Posted on February 14, 2025 by Rob Carek, Vice President, Client Solutions
Non-gaming accounts for nearly 17% of total casino revenue, according to the American Gaming Association, but in some cases, it can contribute as much as 70%. That’s a substantial differential, and it demonstrates just how large the opportunity is for casino operators to drive revenue growth through non-gaming channels. In fact, the 2024 LaneTerralever (LT) Non-Gaming Player Insights Report indicates that across all age and income demographics, non-gaming activities and amenities like restaurants, bars, spas, bowling alleys, arcades, and live entertainment, are an important consideration in determining which casino to go to.
For years, casino operators have known that personalized experiences build loyal customers and that player’s clubs and loyalty programs provide valuable data on gaming habits. But they miss a crucial piece of the puzzle—non-gaming spending. As these experiences become increasingly meaningful to guests, how can casinos gain a complete view of customer behavior and drive revenue growth across their entire property?
GenAI is here to help.
By leveraging your existing loyalty program and other data, along with GenAI, you can gain deep insights into non-gaming guest behavior, enabling highly personalized recommendations and incentives that encourage exploration of all the amenities on site.
And Kopius has a Virtual Concierge solution to make it happen.
The Who, What, Where, and Why of Non-Gaming Casino Revenue
While gaming remains important to consumers across all demographics, individual preferences, behaviors, and importantly, the opportunities for casino operators vary widely based on generation and income. The LT report indicates that:
All demographics are increasingly going to casinos in groups, and 70% of them say that non-gaming activities are more important when they are with a group.
79% of affluent consumers consider non-gaming offerings in choosing a casino and are more likely to spend 50% of their time engaged in non-gaming activities, and are particularly interested in live events.
86% of Gen Z consumers visit local casinos in groups. When visiting a destination casino, non-gaming amenities like restaurants and live entertainment are top priorities, but at 14%, they allocate the least amount of total spending to non-gaming relative to other generations.
Non-gaming activities are more important to millennials than to any other generation, with 89% of them saying they have a significant impact on which one they choose and 69% saying they budget specifically for non-gaming.
Only 34% of Gen X consumers say that non-gaming activities impact their loyalty to a casino, but like their boomer and Gen Z counterpart, food matters. Gen X prioritizes non-gaming spending in restaurants.
41% of boomers factor in non-gaming activities when choosing a casino, and they allocate 18% of their spending to them. For boomers, restaurants and bars are the most important non-gaming activity.
Insights like these are incredibly powerful when developing non-gaming offerings for specific demographics. But imagine if you could target offerings even more closely, based on individual casino guest preferences and behaviors. And imagine that based on choices guests made during previous visits to your casino, you could anticipate the types of non-gaming activities they might enjoy during future ones. How would that impact the guest experience? And what would that do for your business in terms of loyalty and increased revenue.
GenAI can close that gap, and it isn’t just a promise of what’s to come—the technology is available today.
The Kopius Virtual Concierge —Personalized Recommendations that Drive Non-Gaming Revenue
The Kopius Virtual Concierge for casinos is a flexible, GenAI-powered app that delivers personalized recommendations, incentives, and service to your guests. It connects to your existing data sources like players clubs, loyalty programs, reservation systems, and builds on that data as guests use non-gaming services. With the Kopius Virtual Concierge, you get a comprehensive view of guest behavior across your entire property, not just on the gaming floor, so you can optimizing your non-gaming offerings for maximum impact.
With the Kopius Virtual Concierge, you will:
Boost dining revenue: Offer targeted deals and recommendations based on guest history and preferences, driving traffic to your restaurants and increasing spend.
Upsell related services: Proactively suggest relevant offerings based on guest bookings and activities—like a golf lesson after a tee time—increasing revenue per guest.
Craft tailored itineraries: Create personalized plans based on past visits, encouraging longer stays and maximizing guest engagement and spending.
Optimize offers with data: Leverage real-time data and guest feedback to refine promotions and personalize experiences, driving non-gaming revenue growth.
The possibilities are endless.
Imagine a casino experience perfectly tailored to each guest. That’s the power of the Kopius Virtual Concierge. The more guests engage with it, the more personalized their experience becomes. Meanwhile, casino operators gain access to invaluable data on guest preferences, creating a continuous feedback loop for optimizing offers and experiences.
Elevate Guest Experiences and Drive Non-Gaming Revenue with the Kopius Virtual Concierge
At Kopius, we harness the power of people, data and emerging technologies to build innovative solutions that help our customers navigate continual change and solve formidable challenges.
JumpStart Your Technology Project—and Stay on Track—with Kopius!
At Kopius, we harness the power of people, data and emerging technologies to build innovative solutions that help our customers navigate continual change and solve formidable challenges. To accelerate our customers’ success, we’ve designed a JumpStart program to prioritize digital transformation together.
Posted on January 30, 2025 by Danny Vally, Chief Operating Officer, Kopius
Female freelance developer coding and programming. Coding on two with screens with code language and application.
According to Deloitte’s 2024 Mapping Digital Transformation Value report, there is a sea change in how companies are investing their innovation budgets. Fewer dollars are being invested in transformational change. Instead, “Budgets are going toward more concrete business cases: entering new markets, launching new products, and modernizing the core.”
And a primary driver for this change is value.
The survey indicates increased investments technologies respondents perceived as driving the most value—GenAI, traditional AI, and data architecture are chief among them.
Overcoming Innovation Ambiguity and Identifying Value
Innovation is inherently ambiguous. It is in complete opposition to a concrete business case. You may have a concrete problem but be unclear about whether or how an emerging technology can solve it. Or maybe you know you need to start experimenting with new technology, but you haven’t defined what it can do for your organization. Both those scenarios are a long way from a business case and even further from demonstrating value.
So how do you bridge the gap?
While it may seem counterintuitive, putting some structure around the innovation process can be advantageous, particularly when it comes to narrowing in on a business case and demonstrating value. It can provide you with space to think things through, home in on a problem, and explore solutions from several different angles. It can unearth the unknowns and root out costly gotchas that might prevent you from moving forward. A structured innovation process provides an opportunity to figure out if something.
Innovation often ends with proof of concept that demonstrates that something can be done. That may solve the business-case challenge, but it’s not enough show value. Proof of value is a more modern approach. Proof of value is about more than if something can be done—it’s about whether it should be done. It’s intended to show whether it solves your business problem, is financially and operationally viable, and what it will take to pilot and scale.
JumpStart—A Value-Based, Guided Process for Technology Innovation
Kopius’ flexible future state and product ideation program, JumpStart, is a framework for innovation designed to help you explore possibilities, narrow down business use cases, and demonstrate value. And while JumpStart is a great launchpad for exploring both traditional and GenAI, it’s also a good fit for other types of innovation. Manufacturing, healthcare, and retail organizations, for example, may want to get a better understanding of their physical environment through IoT. And companies of all types have ideas for digital products they’d like to develop, but just don’t have the capacity.
JumpStart is technology agnostic—often, the solution to a particular challenge includes many integrated approach involving AI, IoT, AR/VR, etc.
The possibilities are endless.
Regardless of what you’re interested in exploring, the foundational process is similar, and typically entails—and it typically wraps up with a proof of value.
Research – First, we explore emerging trends in your space, how early adopters in are using new technologies, and what’s happening in other industries that might be applicable.
Dialog & Discovery – Next, we bring all the key stakeholders to the table to explain any relevant new technology, present the research, and discuss challenges and opportunities.
Brainstorming & Whiteboarding – Then, we brainstorm and whiteboard potential solutions, prioritize by need and impact, and provide space for you to consider next steps.
Proof of Value – Last, we bring together a team to prototype a solution that tangibly demonstrates whether something can be done, and what it will take to make it happen.
The goal of the JumpStart process is to for you to have the information you need to determine if the innovation path you are considering makes sense—whether it’s achievable, what the business case is, what the obstacles are, and if it will drive value for your organization.
While JumpStart typically ends with the proof of value, it’s rarely the end of the project lifecycle. If you’re looking to launch a pilot initiative or scale a program or technology across your organization, we can help with that, too.
JumpStart in Action—Three Real-World Examples of How
Innovation looks different.
To get a better understanding of how JumpStart future state and product ideation workshops can help you innovate and solve your most pressing challenges, I’ve pulled together three real-world examples.
An AI solution for triaging automotive warranty claims – A leading auto manufacturer with a large warranty business wanted to explore how AI could help them triage claims. They needed to understand if it was a practical solution and what implementing it would entail. The JumpStart and proof of value process proved their idea was achievable, but it brought to light some underlying issues around data and integrations. They came away with not only a better understanding of what was possible, but also what it would take to get there.
An IoT solution for monitoring vaccines storage temperatures – A global healthcare nonprofit that provides vaccines needed to monitor the temperatures of refrigerators in remote locations with inconsistent power supplies to ensure the vaccines’ efficacy. The JumpStart and proof of value process was the launchpad for a viable solution that included everything from building a circuit board, to operationalizing it with 1G connectivity in the Azure Cloud. Once the initial project was a starting point for a host of related solutions, including refrigerated backpacks and fanny packs.
A competitive gap analysis for a robotics company’s app – A manufacturer of robotic household appliances wanted to benchmark their app experience and physical against their competitors’ solutions. They needed objective real-world insights into their strengths and opportunities for improvement, so they knew where to focus future development efforts. The JumpStart and proof of value process led to tangible enhancements to both their app and product that improved customer experience.
JumpStart Your Technology Project—and Stay on Track—with Kopius!
At Kopius, we harness the power of people, data and emerging technologies to build innovative solutions that help our customers navigate continual change and solve formidable challenges. To accelerate our customers’ success, we’ve designed a JumpStart program to prioritize digital transformation together.
Posted on January 30, 2025 by Danny Vally, Chief Operating Officer, Kopius
Male IT Specialist Holds Laptop and Discusses Work with Female Server Technician. They’re Standing in Data Center, Rack Server Cabinet with Cloud Server Icon and Visualization.
Enterprise technology adoption typically follows an S curve, with organizations first undertaking frontier innovation, then experimenting, piloting, and scaling, as McKinsey explains in their latest Technology Trends Outlook. But innovation has never been easy, and staying ahead of the emerging technology frontier is an infinite race. It’s hard to take care of today’s problems when you’re focused on tomorrow. Consider AI or GenAI—you may not have in-house expertise, or if you do, their efforts are focused on existing programs. Maybe you just don’t have the time and space to figure out what types of problems emerging technologies can solve and what the best use cases are in your business.
To take advantage of AI and GenAI, innovation and experimentation are necessary first steps. It’s the only way to figure out what’s going to work for your company and to get buy-in before investing.
That’s why more companies are looking to external partners for help.
Technology Experimentation and the Art of the Possible
When IoT was first introduced, it was complicated, and companies didn’t know what it meant for their businesses. So, at Kopius, we started holding future state workshops to help our clients understand what it was all about, the types of problems it could solve, and to identify some specific use cases within their businesses. We quickly came to think of it as the art of the possible.
We’re seeing much the same thing with AI, and to meet the need, we’ve designed a full-fledged innovation and experimentation service offering we call JumpStart.
Our JumpStart process provides a roadmap for frontier innovation and experimentation. It entails:
Research – Over the years we’ve learned how valuable it is to come to the table with a big picture understanding of your business, what the emerging trends are in your space, how early adopters in your industry are using it, and even if other industries are using it in ways that might be applicable.
Dialog & Discovery – Once we’ve wrapped our heads around all that, we bring all the key stakeholders to the table to explain the technology and present the research, which then generates good discussions about the business problems you’re having and opportunities you could potentially take advantage of.
Brainstorming & Whiteboarding – This is where the art of the possible comes to life. Using a design thinking approach, we brainstorm and whiteboard potential solutions to your most challenging problems and opportunities. Then, we prioritize them based on greatest need and impact. We also give you some space to think about what the best opportunity to move forward with is.
Proof of Value – The last step of the process is to demonstrate proof of value. We bring together a multi-functional team to do some light, rapid prototyping that tangibly demonstrates the use case. Proof of value isn’t just about whether something can be done—it’s about whether it should be done. Does it solve your business problem? Is it financially and operationally viable? What will it take to pilot and scale?
While the proof of value typically marks the end of the JumpStart process, it doesn’t necessarily mark the end of our partnership. For many of our clients, it’s just the beginning. Kopius can also pull together the right resources to pilot the project and scale it across your organization.
JumpStart in Action – For a Leading Auto Manufacturer, JumpStart Brought Critical Information to Light
A leading auto manufacturer with a large warranty business wanted to use AI to make more informed decisions about what claims to automatically approve vs. look into more deeply. Before fully investing in the project, they needed to better understand if it was a practical solution and what implementing it would entail.
After some initial research, we brought key stakeholders to the table for in-depth discussions about the possibilities, the opportunities, and their business challenges. Then, we brainstormed and white boarded potential solutions. A big part of this was mapping out a detailed service blueprint that detailed every step of the warranty claim process.
Next, we tackled the proof of value, which brought critical information to light. While the AI solution was possible, they needed to address some upstream challenges before it could be implemented. Since claims were being submitted by so many different people through so many different systems, they would first need to build integrations and standardize the way data was coming in.
This gave the auto manufacturer the necessary insight to weigh the effort and expense vs. the long-term benefits of the undertaking and make an informed decision about moving forward.
The Value of a Fresh Perspective
When you are laser focused on solving today’s problems, it’s hard to break away and orient yourself to the larger world of advancing technology. That’s why an external technology partner like Kopius can be a real asset. We bring fresh perspectives, objectivity, and use cases from within your industry and outside of it to help you drive innovation, experiment, pilot, and scale.
Wherever you are on your AI innovation journey, we’d love to help you explore the art of the possible.
JumpStart Your Technology Project—and Stay on Track—with Kopius!
At Kopius, we harness the power of people, data and emerging technologies to build innovative solutions that help our customers navigate continual change and solve formidable challenges. To accelerate our customers’ success, we’ve designed a JumpStart program to prioritize digital transformation together.
Posted on January 23, 2025 by Hieu (Sam) To, Manager, UX/UI Design
Design thinking is about empathy—putting yourself in another person’s shoes to solve a problem they are facing. User-centered design is about, well, useability. It narrows in on the part of that solution that is tied to a digital or online experience, whether that’s a product, an application, or a website. The two concepts go hand-in-hand, and as Kopius went about building Tucson Medical Center’s (TMC Health) digital front door, both were at the forefront of our thinking.
The reason? Trust.
It’s important for people to be able to trust their health care system and its providers. And we wanted to send that message loud and clear in every digital interaction. Empathy and useability were the keys.
Key Strategies for Overcoming Complexity
Healthcare can be complicated, overwhelming—even scary. A digital front door, which is an online portal or platform where a health care system, its staff, patients, and even their families or other caregivers, can easily interact and access the information, should be designed to make it less so. Design thinking and user-centered design drove every aspect of our approach to building the new site, which we did using the Payload content management system.
Among the many strategies we used, three stand out. First, every decision we made was centered on the user journey, which was a bit tricky, since there was more than one user. Second, we made access to critical information as straightforward as possible. And third, we used visual branding to simplify and guide users.
While these are particularly critical in a health care setting, they are truly universal and applicable when developing any digital product or solution.
1. Prioritize the User Journey—Even on the Backend
When developing any digital product, the user journey should always be your top priority. But in TMC Health’s case, they needed to welcome both new and established patients, and their journeys are very different. For example, new patients are often looking for educational and marketing materials about what the health system offers while returning patients need to quickly find specific services and providers, schedule appointments, etc. We had to create pathways for both.
Digging deeper, we realized those aren’t the only two user personas that matter. TMC Health’s team uses the site to upload and manage content. They had their own user journey that had to be addressed. Not only did we need to structure the backend so they could work efficiently, but we also needed to build guardrails so that they uploaded new content, they didn’t make changes that would impact the user experience.
Websites often must address the needs of more than one user persona, both on the front end and the back. You may not be able to tackle everything at once. That was the case with the TMC Health project, so we took a phased approach. First, we addressed the established patient journey, then the needs of new patients.
2. Make Sure Important Information is Just Two Clicks Away
TMC Health’s previous website grew to include more than 1,300 pages of content. It was a maze to navigate. Our challenge was to simplify it so people could find what they needed with minimal effort. We started by conducting a content audit and inventory, then we built a restructured site map with improved hierarchy that prioritized important information. We also condensed content and sunset out of date information. In the end, we were able to get those 1,300 down to about 400, so that no critical information was more than two clicks away.
Next, we turned our attention to TMC’s internal users. To make sure they could add necessary content without overwhelming the site or patients using it, we developed content writing guidelines tailored for healthcare that focus on clarity, accessibility, and relevance. Then, we streamlined the back end to make it simpler for content writers to manage and update information across the network and reduce the need for training. We also added formatting and character count limits in the CMS to ensure new content was concise and is easy to skim.
While finding the information you need fast is critical when your health is on the line, it’s true on any website. Many companies, especially in the business world, overcomplicate their sites—they want potential customers to spend time on it. But I would caution to pick your moments. Customers come to your site for many reasons—sometimes they need information fast, and other times they’re there to learn. Prioritize accordingly.
3. Use Visual Branding to Create Cohesiveness—and Differentiation
TMC Health is comprised of 10 clinics and facilities. On their previous site, these were all visually branded the same. Typically, consistent branding is a best practice, but in this case, it created confusion for users. Our challenge was to find a way to create alignment with the primary TMC Health brand structure while making it easy for people to quickly differentiate between locations. We solved this by developing an overarching color scheme and using different but visually related colors for each location. Importantly, though, we kept the page layout consistent so users could quickly find or navigate to the information they needed.
This situation isn’t exclusive to healthcare—large corporations with multiple lines of business often face similar challenges. The big takeaway here is that color can provide cohesiveness, but in a situation where everything else is consistent, it can be a differentiator that helps the user—in this case a patient—quickly understand that they are in the right place.
Design Thinking: Empathy Builds Trust
Patient care begins at the digital front door. It’s a healthcare system’s first opportunity to build trust and demonstrate the level of care people can expect throughout their healthcare journey, from routine family care to urgent help in an emergency. A digital front door built on a solid foundation of design thinking and that prioritizes the user journey, can make a real difference in moments that matter, perhaps even saving lives.
JumpStart Your Technology Project—and Stay on Track—with Kopius!
At Kopius, we harness the power of people, data and emerging technologies to build innovative solutions that help our customers navigate continual change and solve formidable challenges. To accelerate our customers’ success, we’ve designed a JumpStart program to prioritize digital transformation together.
Posted on November 5, 2024 by Diego Anfossi, Vice President of Delivery, and Matias Mazzucchelli, Managing Director
Everywhere you go, emerging technology like generative AI (GenAI) is top of mind. Organizations are wisely racing to incorporate it into their workflows to gain insights and efficiencies that will drive customer value and give them a competitive edge. But many of the fundamental challenges that faced IT and development teams prior to the advent of GenAI remain, and chief among them are simply bandwidth and budget. In fact, in the Skillsoft 2023-2024 IT Skills and Salary Report, more than 5,700 respondents identified resource and budget constraints as the number one challenge their organizations face.
At Kopius, we hear this from our clients every day. Your senior team members are so bogged down with day-to-day responsibilities, they don’t have the time to address emergent business needs, much less innovate. But adding headcount is both time-consuming and costly. It takes time and effort to find the right people with the right skills. You don’t always have the budget for full-time staff, or you may only need extra help for a short period of time.
At Kopius, we are excited to introduce Kopius Labs, a new resourcing solution designed to meet you where you are, so you can quickly and cost effectively stand up a team for a pressing, usually short-term project.
Your Team, Your Way—Flexible and Cost-Effective Blended Talent Teams
If you’ve worked with Kopius before, you know our team of inspired realists is our superpower. What you might not realize is how much work we put in behind the scenes to identify the best talent. And we don’t stop there—we also provide continuing education to make sure they’re always at the top of their game. Our near shore, LatAm-based teams are a blend of experts in a broad range of technologies and principles, people with solid, mid-level experience, emerging talent fresh out of Kopius Academy, our certification program, and everything in between.
If you have a small project or short-term need, we can quickly and cost effectively stand-up a Kopius Lab—a team of people with blended levels of expertise, some who are between longer term projects, to close the gap.
Kopius Labs is a win-win for both you and our team members. You benefit from rapidly advancing design thinking, accelerated feature development, and groundbreaking R&D work, and our teams gain rewarding opportunities and valuable experience working on cutting edge projects. All of this is delivered through a cost-effective, blended team structure, ensuring high-impact results without the expense of high-priced resources.
Just tell us what problem you’re trying to solve, and we’ll spin up a custom Kopius Lab to resource it.
Kopius Labs—A Right-Sized Resource Solution
At Kopius, we’re still focused on digital leadership: developing digital products and custom applications powered by technology, data, and IoT. And we still deliver services through all our usual resourcing approaches: future-state workshops, end-to-end project delivery, managed services, and with embedded team members. Now, with the addition of Kopius Labs, we can help our customers quickly fill technical gaps between those larger scale and longer-term projects.
Here are just a few ways Kopius Labs can help:
Managing Daily Operations Every company has operational upkeep—tasks you must do to keep things running smoothly. But it shouldn’t keep your senior team members from contributing where you need them most. Kopius can spin up a Lab to handle the everyday so you can use your team more effectively.
Addressing Emergent Needs No matter how well you plan, something unexpected always comes up. Need to quickly ramp up your technical resources to handle an ad hoc project or augment your team during busy season? Kopius can spin up a Lab so you can scale your team quickly.
Experimenting and Innovating Sometimes, you just need to understand if something is the right approach for your company. Looking to explore a new idea, test something quickly, or whip up a quick proof of concept? Kopius, can spin up a Lab to make sure you’re headed in the right direction.
Kopius Labs is all about scale, flexibility, and speed—at a competitive price, of course.
Innovate and Scale—Quickly and Cost Effectively—with Kopius Labs!
At Kopius, we harness the power of people, data and emerging technologies to build innovative solutions that help our customers navigate continual change and solve formidable challenges. To accelerate our customers’ success, we’ve designed Kopius Labs so you can innovate and scale quickly and cost effectively
Posted on November 5, 2024 by Rob Carek, Vice President, Client Solutions
There is so much intellectual consideration given to the application development lifecycle.
Methodologies like Agile, DevOps, and DevSecOps, which are designed to drive more value by getting new features and enhancements to market faster, with fewer issues, are evidence of this. But very few people think about managing the code lifecycle, at least not beyond a single product. We often just accept the limitations and inefficiencies around code development.
AI-fueled CodeOps is here to change that.
CodeOps is designed to relieve developers of repetitive coding so they can focus on higher level work and accelerate the velocity at which they can get new features and enhancements to market.
Repetitive Coding—and Testing—Is Inefficient
Companies typically align development teams to a single product, and those teams rarely branch outside their own area of focus. The approach has both advantages and disadvantages. On the upside, developers have greater context for their work. They know their products and can build on code they created. The downside, especially for companies with multiple products, is that developers waste large amounts of time writing code that does things that already exist within other products. They’re writing code to do the same thing again and again.
It’s wildly inefficient.
And it’s just not developing code—it’s testing it, too. You develop the code, you develop the test code, you identify and address issues, you release, you fix bugs. The inefficiencies grow exponentially, especially across multiple products. You can see how this might open the company to greater exposure from a security standpoint, as well.
But what if you could find similarities between requirements, develop code to address them, and use it everywhere those requirements exist? What impact would it have on your company, customers, and development teams?
CodeOps Accelerates Velocity—and Value—at Scale
Enter CodeOps.
CodeOps is a methodology that prioritizes reuse of existing code wherever possible. Organizations can use it to reduce development time and get new products, features, and enhancements faster and more securely by reusing, repurposing, or building on code they already have. It entails adopting new ways of thinking, putting new practices and processes in place, and using technology like GenAI to match requirements with reusable, modular pieces of code stored in a code library, so new code is written only when it’s not in the library and/or is truly unique to a single product.
The obvious gains are consistency, efficiency, and security. Products are more structurally similar, and developers aren’t spending hours recoding the same thing dozens of times—or testing it. You already know it works. If your organization uses DevSecOps practices, you know security was a primary consideration in its development. And if there is an issue, once a patch is deployed, it is fixed everywhere it is in use.
But CodeOps is more than just an efficiency play. By using code from the library, even as a starting point, developers can put more time and effort into coding things that are going to have a big impact on your products—things that drive value to your customers and create value for your company. And from a developer’s perspective, that is more interesting, rewarding, and desirable work.
As with agile, DevOps, and DevSecOps, CodeOps requires cultural and process changes. Developers must adopt new ways of working, but they also must be willing to trust the code.
Ignite CodeOps Adoption with an External Catalyst
All the major code platforms—Jira, GitHub, Azure DevOps, Slack—are actively exploring how to integrate CodeOps into their solutions, and third-party tools are emerging, as well. They are all nascent, with some working better than others, which makes it difficult to determine which one will best serve you in the long run. In addition, adopting CodeOps is more than just bolting on a technology solution. Like Agile and DevOps before it, CodeOps requires a cultural shift. Developers must adopt a new mindset and new ways of working. And they must learn to trust the existing code modules enough to incorporate and build on them.
These technical, organizational, and cultural barriers make it challenging to figure out how to get started, especially when your teams have so much to do. Sometimes, it takes an external catalyst to make CodeOps real. At Kopius, we’ve developed a solution to help organizations adopt CodeOps without having to tackle the organization and cultural transformation or make a long-term commitment to a platform that is still figuring out its approach.
First, we use GenAI to intelligently review your backlog and identify commonalities in new requests. Next, we aggregate those requests and develop requirements to address them. Then, we develop code to cover the bulk of those commonalities and validate it with your developers to get their feedback and buy in. The code is stored in the code library and pushed to the right code repositories. Then, when you’re ready to tackle one of those new requests in a sprint, your developers simply pull the relevant code from the repository and use it as-is or as a starting point. As additional new requests come in, the process is repeated.
Companies gain the advantages that come with looking at code across their entire portfolio and maintaining it by feature and functionality, without disrupting existing development processes.
It’s a smart point of entry for any organization wanting to get started with CodeOps today.
CodeOps: A GenAI Approach to Working Smarter, Not Harder
Ultimately, CodeOps solves a fundamental problem that many organizations have—writing the same requirements and code for multiple products. It’s a hard challenge to overcome because the organizational constructs inherent in development teams lend themselves to a product-by-product approach.
But with a little help from GenAI and an external catalyst like Kopius developers can work smarter, not harder and accelerate the velocity at which they can deliver value.
JumpStart Your Technology Project—and Stay on Track—with Kopius!
At Kopius, we harness the power of people, data and emerging technologies to build innovative solutions that help our customers navigate continual change and solve formidable challenges. To accelerate our customers’ success, we’ve designed a JumpStart program to prioritize digital transformation together.
Posted on October 28, 2024 by Kopius Editorial Board with Rob Carek
Rob Carek Explains Why CodeOps is a Win for Businesses, Customers, and Developers
Across the enterprise, in every industry vertical and every operational and functional area, organizations are racing to take advantage of Generative AI (GenAI). It’s already in use in 65% of organizations, according to a McKinsey Global Survey. For software companies, much of the focus has been on using GenAI to generate code. But the approach has challenges. Depending on the tool developers use, the code accuracy rate is only between 31% and 65%, according to a Bilkent University study. The general consensus is it’s buggy and poses hidden security risks.
But software companies and developers now have another meaningful approach to GenAI at their disposal—CodeOps. GenAI fueled CodeOps is an approach that now enables developers to reuse internally owned, fully approved, modular coding building blocks—systematically. And it’s driving a transformational shift that creates business and customer value, unburdens developers of mundane and repetitive coding, and enables them to innovate.
We sat down with Rob Carek, Vice President of Client Solutions at Kopius, to introduce you to CodeOps.
Tell me about CodeOps. What is it and what problem does it solve?
Modern software development processes are wildly inefficient. A fundamental challenge, at least for companies with more than one product or application, is that there’s no practical way to reuse code. So, if you have a suite of 20 products, and every single one of them has a similar feature, your development teams have built that feature 20 different times—and they do it differently, every single time. In theory, a human could pour over requirements and search code repositories to find commonalities and reuse existing code, but that’s just not practical—it would be far more work than just rebuilding it.
But with the advent of GenAI, code reuse is NOW an addressable problem.
CodeOps is a code reuse strategy, and GenAI is not only the enabler, but also the accelerator. The idea is that companies can now develop reusable, modular code and store it in a library or repository. Then, GenAI can be used to search for existing code to use or build on instead of developing everything from scratch.
What are the big benefits of CodeOps?
There are four big benefits that I see: efficiency, innovation, faster time to market, and security. From an efficiency standpoint, since existing code is being repurposed, companies can save a ton of development and testing time. And when you think about how that is amplified across a whole suite of products—well, the gains are almost exponential. And all the time they save, they can spend innovating—building new features and enhancements that are unique to a given product and require original code. It’s the more challenging and interesting part of a developer’s job and where they really want to spend their time, so there’s a human benefit. It also means that things that really move the needle get to market and in customers’ hands sooner.
From a security standpoint, anything in the library is proven code—you know it meets organizational security and compliance standards. But, again, the impact really comes at scale. If you push a patch, everything updates, every vulnerability is closed wherever the code is in use.
Is CodeOps compatible with DevOps and DevSecOps?
Absolutely. The goal of DevOps is to break down silos between development and operations so new products, features, and enhancements get to market faster, more efficiently, and with fewer issues. DevSecOps prioritizes security at every step of the process. But both practices are focused on code development at the product or team level. CodeOps addresses a need at the organizational level, across multiple products. By reusing code wherever possible, CodeOps amplifies DevOps and DevSecOps outcomes—new things get to market even faster, even more efficiently, and with even fewer issues.
How can organizations get started with CodeOps?
Many of the major code platforms are starting to explore CodeOps and looking for ways to integrate it into their solutions, but it’s still very early days. I anticipate the first place they will start is using LLMs to identify commonalities in requirements. That doesn’t account for developing code that fulfills those requirements, and it’s going to be a long while before we see integrated, searchable code libraries. But that doesn’t mean you have to wait until they figure it out to get started.
At Kopius, we’ve developed a solution companies can use to adopt CodeOps today. We use GenAI to look at your backlog and identify commonalities in new requests and aggregate them. Then, we develop requirements and develop code to address them and validate it. The code is pushed to your code repository so when you’re ready to work those requests into a sprint, your developers can access it. It’s a more organic way to build a library of existing, pre-approved code that doesn’t require your teams to operate any differently than they do now.
What will it take to get developers to adopt CodeOps?
Modern development practices are simply not designed for content reuse at scale—there’s no precedent for it. And culturally, developers will look at someone else’s code and think, “I wouldn’t have done it that way.” So, like DevOps, getting developers to adopt CodeOps is going to take cultural change. Kopius’ solution takes that into consideration. It’s a hybrid human / technology approach that builds trust and buy-in by actively engaging developers in reviewing requirements and code and providing feedback. That way, they’ve contributed to it and have more confidence in it.
And as I mentioned earlier, CodeOps frees developers from the repetitive and mundane—things that are table stakes, so they have more time for developing things that are truly innovative. It’s a win-win.
What’s the single, most important thing companies should know about GenAI-fueled CodeOps?
GenAI-fueled CodeOps isn’t just an incremental improvement. It’s a truly transformational shift that will enable organizations to develop code at speed and scale, drive value into customers’ hands at speed, and free developers from the burden of repetitive, mundane work so they can focus on innovating.
Ultimately, GenAI-fueled CodeOps makes the most of what both technology and humans bring to the table—and rapidly scales it.
JumpStart Your Technology Project—and Stay on Track—with Kopius!
At Kopius, we harness the power of people, data and emerging technologies to build innovative solutions that help our customers navigate continual change and solve formidable challenges. To accelerate our customers’ success, we’ve designed a JumpStart program to prioritize digital transformation together.
Every technology project starts with an outcome—a business goal that needs to be achieved. But to achieve that goal, you need to define a set of deliverables, establish a timeline, and determine a budget. Rarely do the timeline and budget line up with the work that needs to be done. There are seldom enough dollars to put the number of people on the project necessary to bring the deliverables to life within the timeline. This is often because of how challenging it is to fully scope a project up front. No matter how thorough you are, new requirements come to light, resulting in scope creep.
Many companies will lean into project management to make everything come together. Smart—a solid PMO practice is the foundation on which all successful technology projects are built.
But you can’t always project manage your way out of this type of problem. That said, there are some things you can do.
Two Key Approaches to Use When Time and Budget are Out of Sync with Project Scope
One of the most complex technology consulting programs I’ve worked on was for a new company in the healthcare space. The budget was a swag from an investor’s presentation deck and was completely out of alignment with the six-month timeline for standing up ERP manufacturing system, provider and patient registration and management portals, and an ecommerce app. Rescoping the project wasn’t an option—if every compliance parameter wasn’t met within the given timeframe, the client would have to wait an entire year to reapply with the organization that had program oversight. In the end, we met the timeline, stayed on budget, and our client was awarded the contract they were after.
We used two key approaches to make it happen. First, we brought all the right stakeholders to the table early to develop standard operating procedures (SOPs). And second, we used those SOPs, as well as compliance guidelines, to build and validate wireframes before standing up MVPs. Then we validated those before coding the actual apps.
Engage the Hive Mind
At the beginning of the initiative, we brought all the key stakeholders together for a series of workshops—one for each app we had to deliver. Every department that had a say was represented—product, engineering, sales, marketing, manufacturing, and legal. Not only did we have a binder on hand detailing hundreds of pages of compliance regulations, but we also had someone on hand who knew them inside and out. Collectively, we walked through every aspect of each app, developing standard operating procedures, strawmen, and requirements.
This hive mind approach meant we could problem solve, make decisions and come to agreements at speed and minimized our chances of going down the wrong path.
My Take
When timeline and budget aren’t in line with the work that needs to be done, you can’t afford to make mistakes. Get the people who hold the answers to your questions in a room and map out your requirements. At Kopius, we call these JumpStarts, and they may take a few days or a few weeks. Then, continue to check in with the same stakeholders at every critical juncture to validate your work.
“Measure once. Cut twice.”
For me, the project management equivalent of “measure once, cut twice,” is wireframes first, MVP second, coding third. And at each of these stages, you need to bring your stakeholders together to validate your work. For the healthcare project, once we had a thorough list of requirements, our UI/UX developed wireframes that we validated with the same group of stakeholders we initially brought to the table. This allowed us to identify and work through any potential issues up front. Then, once the wireframes were validated, we stood up MVPs for each app so stakeholders could walk through the basics of each process and validate it. Only then did we dive deep into coding all the features and functionality for the first release.
My Take
When timeline and budget aren’t in line with the work that needs to be done, the inclination can be to jump right into coding. A better approach is to double down on validating your path forward through JumpStart workshops and wireframing. This will minimize errors—and added time and costs—in the long run.
Expect the Unexpected
No matter how thorough you are in developing your requirements, there are going to be some “ahas” along the way. You have to expect the unexpected and remain flexible. But being flexible doesn’t mean saying yes to everything. Scope creep can derail a project from both a timeline and budget standpoint. For this project, we managed that by getting everyone to agree to a light phase one for each application, then planned to iterate, releasing new features every two weeks after launch.
Looking Ahead: The GenAI Approach
Like many technology companies, Kopius is actively integrating generative AI (GenAI) into our processes, and I’m working on a set of custom GPTs that I believe can make a difference when time and budget are out of sync with requested deliverables. By entering business and technical requirements into it—maybe even a transcript from a discovery session—and asking it to generate common use cases that serve as starting points for designing application features, we can streamline the work involved in building new apps. The prompt engineering requires a lot of up-front effort, but once that initial lift is done, we’ll be able to use it again and again.
Undoubtedly GenAI will deliver thousands of small efficiencies like this, but it’s only part of the equation. The time / budget / scope challenge is an inherent part of software development, and solving it is always going to take a multi-faceted approach.
JumpStart Your Technology Project—and Stay on Track—with Kopius!
At Kopius, we harness the power of people, data and emerging technologies to build innovative solutions that help our customers navigate continual change and solve formidable challenges. To accelerate our customers’ success, we’ve designed a JumpStart program to prioritize digital transformation together.
Generative AI (GenAI) adoption is surging. Sixty five percent of respondents to the McKinsey Global Survey on the State of AI in Early 2024 indicate their businesses are using generative AI in at least one functional area. Yet, more than half of individual GenAI adopters use unapproved tools at work, according to a Salesforce survey. Clearly, businesses want and need to implement the technology to meet their business goals, but in the absence of a clear path forward, employees are finding ways to adopt it anyway, perhaps putting sensitive data at risk. Organizations need to move fast, put a strategy in place, and implement pilot projects with impact.
But what’s the best way to get started?
We get this question often at Kopius. Maybe you have a problem you need to solve in mind or a general use case, or maybe that’s not yet clear. You might understand the possibilities but haven’t narrowed down an opportunity or area of impact. Regardless of which camp you’re in, when we peel back the onion, we find that most companies need to step back and address fundamental issues with their data foundation before they can begin to tackle GenAI.
At Kopius, we have a detailed framework for walking you through the things you need to take into consideration to identify a GenAI pilot project and build a data foundation to support. But asking—and answering questions like the ones below—is at the root of it.
What problem are you trying to solve?
In a survey of Chief Data Officers (CDOs) by Harvard Business Review, 80% of respondents believed GenAI would eventually transform their organization’s business environment, and 62% said their organizations intended to increase spending on it. But no company can afford to make investments that don’t deliver on outcomes.While there is value in just getting started, it’s both worthwhile and necessary to define an initial use case. Not only do you want your program to have impact, but the GenAI ecosystem is so broad that without some sort of use case, you will be unable to define what type of outputs need to be generated.
Some companies will have a clear use case, while others will have a more general sense of where they’re headed. Still others are working with an “AI us” request from senior leadership to explore the landscape.Wherever you are in this process, our framework is designed to help you identify a meaningful pilot project.
What are your data sources? What do you need to capture? Next, you’ll need to take stock of your data sources, so you have a solid understanding of the full set of data you’re working with. What inputs do you have coming in and what inputs do you need to get to your end goal? Often, there is a project behind a project here. If you don’t have the data you need to solve the business challenge, then you’ll have to develop and implement a plan to get it. For instance, say you want to measure the impact of weather conditions on fleet performance, and you’re planning on using IoT data from your vehicles. You’ll also need to determine what weather data you need and put a solution in place to get it.
What is the state of your data? Is it relevant, quality, and properly housed and structured?
With GenAI, your ability to get quality outputs that deliver on business outcomes depends on the quality of your inputs. That means data must be current, accurate, and appropriately stored and structured for your use case. For instance, if you’re developing a GenAI enabled chatbot that employees can query to get information about policies, procedures, and benefits, you’ll need to make sure that information is current and accurate.
At this point, you’ll also need to consider where the data is being stored and what format it’s in. For instance, JSON documents sitting in non-relational database or tables sitting in a SQL database are not necessarily a model for GenAI success. You may have to put your raw data in a data lake, or if you already have a data lake, you may need to warehouse and structure your data so that it’s in the right format to efficiently deliver the output you want.
What governance and security measures do you need to take? Data governance is about putting the policies and procedures in place for collecting, handling, structuring, maintaining, and auditing your data so that it is accurate and reliable. All these things impact data quality, and without quality data, any outputs your GenAI solution delivers are meaningless. Another important aspect of data governance is ensuring you are compliant with HIPPA or any other regulatory mandates that are relevant to your organization.
Data security, in this context, is a subset of data governance. It is about protecting your data from external threats and internal mishandling, including what user groups and/or individuals within your organization can access what. Do you have PPI in your system? Salary data? If so, who can modify it and who can read it? Your answers to these questions may inform what data platform is best for you and how your solution needs to be structured.
What is your endgame? What types of outputs are you looking for?
The problem you’re trying to solve is closely tied to the types of outputs you are looking for. It’s likely that exploration of the former will inform conversation of the latter. Are you building a chatbot that customers can interact with? Are you looking for predictive insights about maintaining a fleet or preventing accidents? Are you looking for dashboards and reporting? All this is relevant.This also gets into questions about your user profile—who will be using the solution, when and where will they be using it, what matters most to them, and what should the experience be like?
A Rapidly Evolving Data Platform Landscape Drives Complexity
Getting started with GenAI is further complicated by how complex the third-party GenAI, cloud, and data platform landscapes are and how quickly they are evolving. There are so many data warehouse and data lake solutions on the market—and GenAI foundational models—and they are advancing so rapidly that it would be difficult for any enterprise to sort through the options to determine what is best. Companies that already have data platforms must solve their business challenges using the tools they have, and it’s not always straightforward. Wherever you land on the data maturity spectrum, Kopius’ framework is designed to help you find an effective path forward, one that will deliver critical business outcomes.
Do You Have the Right Data Foundation in Place for GenAI?
In the previously mentioned survey by Harvard Business Review, only 37% of respondents agreed that their organizations have the right data foundation for GenAI—and only 11% agreed strongly. But narrowing in on a business problem and the outcomes you want and defining a use case can be useful in guiding what steps you’ll need to take to put a solid data foundation in place.
One last thought—there are so many GenAI solutions and data platforms on the market. Don’t worry too much about what’s under the hood. There are plenty of ways to get there. By focusing on the business problem and outcomes you want, the answers will become clear.
JumpStart Your GenAI Initiative by Putting a Solid Data Foundation in Place
At Kopius, we harness the power of people, data and emerging technologies to build innovative solutions that help our customers navigate continual change and solve formidable challenges. To accelerate our customers’ success, we’ve designed a JumpStart program to prioritize digital transformation together.
Artificial intelligence (AI) is revolutionizing the retail sector, giving businesses greater access to valuable customer data and market insights than ever before. Implementing AI strategies can be highly advantageous for brands looking to meet changing consumer demands and protect their bottom line.
About 40% of retail executives say their companies already use automated artificial intelligence technologies, and 80% say they plan to implement these strategies by 2025. Understanding how your business can utilize AI in retail is key to capitalizing on these solutions for long-term stability, enhanced operations, and profound growth.
Check out the primary use cases and advantages of artificial intelligence for the retail industry below.
8 Use Cases for Artificial Intelligence in Retail
As AI’s popularity and capabilities grow, so do the number of ways your brand can use these tools. Top AI use cases in retail include:
1. Inventory Management
Artificial intelligence can streamline inventory management operations by analyzing historical sales data and customer behavior to accurately predict demand. It can help your retail business maintain optimized stock levels and anticipate trends.
AI-powered inventory management solutions can automate stock replenishment processes, preventing stockouts that frustrate consumers. They also help you avoid overstock situations, identify slow-moving items, and detect anomalies like sudden sales spikes. These insights enable your business to adapt quickly and ensure customers can get the products they want when they want them.
2. Personalized Marketing
AI is an incredible tool for supercharging retail marketing initiatives. These tools and strategies can help businesses deliver personalized campaigns to consumers. Targeted campaigns increase the likelihood of engagement and conversion.
They also enable predictive analytics based on customer data, preferences, and behavior to forecast trends and optimize marketing messages for the greatest return on investment. AI is particularly helpful for identifying the most relevant messages to share at the best time for particular marketing channels.
3. Product Recommendations
By analyzing customer browsing behavior and purchase histories, artificial intelligence can deliver personalized product recommendations that resonate with consumers and increase sales.
AI-powered strategies can automate upselling and cross-selling initiatives for retailers by suggesting complementary products at checkout. Paired with machine learning (ML), AI helps businesses continuously adapt and improve recommendations. They can use consumer feedback to refine the algorithm and increase the likelihood of conversion.
Retailers can also use AI to support personalized shopping experiences and assist consumers while they browse.
4. Automated Customer Service
Automated customer service is among the top examples of AI in retail. Generative artificial intelligence can revolutionize how your business interacts with customers, answers questions, and resolves purchase issues. You can use automated chatbots empowered by natural language processing and ML algorithms that understand and can reply to customer inquiries.
Automated, AI-powered chatbots on your website and social media can help consumers around the clock, reduce administrative burdens on your retail staff, and ultimately improve customer experiences.
5. Predictive Analytics
Retailers can also use artificial intelligence for predictive analytics to accurately forecast future trends, make data-driven decisions, and anticipate customer behavior.
You can train AI models using historical data to predict everything from demand planning to risk management. The AI algorithm can identify patterns and correlations within massive datasets, helping retailers uncover valuable insights to stay ahead of market changes and maintain a competitive edge.
Using predictive analytics insights enables retailers to enhance customer shopping experiences while protecting their bottom line.
6. Pricing Optimization
Artificial intelligence enables retail businesses to develop dynamic pricing models by analyzing various historical and real-time data regarding the following:
Competitor prices
Purchase histories
Market dynamics
Current demand
Inventory levels
Seasonality
Retailers can use AI to maximize profitability and revenue, ensuring you price your products competitively in today’s fast-paced market. Dynamic pricing algorithms utilize machine learning and AI to automate price changes for your business, saving your team time and energy.
7. Supply Chain Optimization
Retailers can also use artificial intelligence to improve supply chain management. After years of supply chain complications and delays, retailers began using AI for real-time monitoring and predictive analytics to support resilience.
AI-powered tools can enhance visibility into logistics operations. This helps businesses choose optimized delivery routes, streamline warehouse processes, and improve supplier relationships. Automated AI solutions and machine learning also allow retailers to achieve:
Increased efficiency.
Lower operating costs.
Minimized human errors.
8. Foot Traffic Analysis
Foot traffic analysis is an advantageous way to use AI in retail stores. Businesses can use AI and machine learning algorithms to track customer movement through a retail space and use that data to optimize store layouts and enhance operational efficiency.
AI solutions can analyze traffic patterns, popular areas, and dwell times to determine what products attract customer attention. Foot traffic analysis data can inform staffing levels and product placements to support better overall shopping experiences.
6 Key Benefits of Using Artificial Intelligence in the Retail Industry
AI can streamline and enhance many elements of running a successful store online and offline. The following are six key benefits of leveraging AI for shopping and retail:
1. Operational Efficiency
Artificial intelligence strategies can significantly improve your retail business’s operational efficiency by automating various time-consuming processes, from inventory management to customer service to supply chain administration. Your business can use different tools and solutions to streamline daily tasks and create smoother processes, making planning and scaling your operation easier.
AI reduces the strain on your team members, giving them more time and energy to enhance your business and help your customers.
2. Reduced Labor Requirements
A huge advantage of introducing artificial intelligence into your retail business is reducing the labor requirements to keep your store running effectively. You can save significant costs and lessen the administrative strain on your team. AI decreases human error, saving your employees and managers time and stress caused by missteps like ordering too much inventory of a particular product.
AI-powered customer service is particularly helpful for your retail team, helping them reduce the time spent answering repetitive inquiries and dealing with basic customer requests. You can rely on chatbots to ease administrative burdens and reduce the number of customer service individuals you need on the job.
3. Enhanced Customer Experiences
AI strategies make it easier for your business to deliver better customer experiences. Automated customer service is particularly helpful for catering to consumer needs and offering them greater convenience. With AI-powered chatbots, your customers can get answers to their questions around the clock. Whether they need to ask about a product or service at midnight or noon, retailers can use artificial intelligence to offer assistance and resolve their inquiries as fast as possible.
4. Increased Profitability
AI and machine learning in retail can help your business become more profitable. In fact, 72% of retailers credit AI for a decrease in operating costs, and 69% attribute an increase in annual revenue to these tools.
Through boosted efficiency and automation, AI enables businesses to boost operational efficiency, productivity, and turnaround times. Retailers can use these solutions to build positive customer relationships, driving increased loyalty, retention, and sales.
5. Personalization
Today’s consumers want personalization and the increased convenience of tailored shopping experiences. Artificial intelligence is invaluable for delivering personalized communications and product recommendations to drive customer engagement and make your shoppers feel special.
AI-powered personalized experiences enable your retail business to cultivate more meaningful and profitable customer relationships. They can drive customer retention, increase conversions, and make shopping at your stores more enjoyable.
6. Competitive Advantage
Artificial intelligence gives retailers a significant advantage over businesses that do not use these solutions. Automated AI enables faster and more accurate processing, analysis, and decision-making. Your business can use AI to quickly identify risks, resolve customer issues, and supercharge inventory management for better operations overall.
Navigating the Challenges of AI in the Retail Industry
While artificial intelligence offers many advantages to retailers, a few hurdles can complicate the integration process:
Privacy and Security
Retailers must prioritize robust data security measures when implementing artificial intelligence solutions. Today’s consumers want to know how you use their personal information and that it is secure. By following strict data protection rules, your business can mitigate the risk of data leaks and breaches.
Different privacy approaches, such as strong access controls and encryption, help retailers overcome these challenges. Through transparency about your AI-related data processes, you can also instill greater trust in your customers.
Data Quality and Integration
Another common pitfall of introducing artificial intelligence into your retail operations is ensuring data quality through smooth integration with other data-collecting systems.
AI models need accurate, consistent data to deliver the most reliable insights to your business. Your AI system likely collects data from multiple sources, and improper standardization practices can lead to disparities, inconsistencies, and errors. Data quality is essential for gaining the most useful and correct insights for important decision-making.
AI Knowledge Gaps
Artificial intelligence technology is new for many individuals. Your team members may not fully understand AI’s key abilities and uses, and some people have misconceptions about these solutions. The knowledge gap can hold your business back.
To capitalize on the many benefits of AI, your retail employees may need training and educational opportunities to help them learn how to responsibly utilize these tools and how they can benefit their daily processes.
Ethical Considerations
AI strategies are not perfect, and you must be conscious of the potential biases in your machine learning algorithm. If bias exists in the training dataset, your outcomes may be unethical and negatively impact certain communities. Ongoing monitoring, refining, and evaluation of your artificial intelligence systems is essential for mitigating bias and ensuring these tools’ most fair and ethical uses for decision-making.
Customer Acceptance
Some consumers are apprehensive about the use of artificial intelligence. Sharing how your business leverages AI and taking full responsibility for its outcomes is essential for instilling greater confidence among your shoppers.
The more your business shares regarding its AI practices, the more consumers will accept it and trust that you are using their data responsibly.
Best Practices for Implementing AI for Retailers
Successful AI implementation requires careful planning. The following are best practices to consider for seamless retail execution:
Define Your AI Objectives
Begin by outlining your business’s goals relating to AI. You may want these solutions to optimize operations, increase sales, or improve customer experiences. Whatever your top objectives are, identify key performance indicators to help measure and track your success. Consider your overall business goals and how AI can support your overarching purpose. These goals should be realistic and achievable, especially at the beginning.
Start Small
The best approach to introducing artificial intelligence into your retail business is to start on a small scale, focusing on specific use cases. Your team can use this opportunity to learn from initial implementations and gather feedback to inform decision-making. It is best to gradually expand your AI capabilities rather than do a massive technological overhaul, which can frustrate your team and customers.
Prioritize Data Quality
Your data needs to be accurate and relevant to support the success of your artificial intelligence initiatives. Prioritize high-quality data by investing in data cleaning, standardization, and enrichment processes. Proper data governance practices will also help your retail business maintain data quality over time, ensuring your insights are valid and useful for informing important decision-making.
Educate Your Team
Providing your team with adequate training, resources, and educational opportunities regarding AI technologies and concepts is key to the most successful implementation possible for retail businesses. Your employees must understand how AI will impact their roles and responsibilities and how to implement your solutions to deliver the best customer experiences. Share your business’s AI objectives, and be transparent about AI’s uses in your business.
Select AI Solutions Carefully
Choose AI solutions for retail with integration, compatibility, scalability, and integration in mind. The systems you work with need to align with your objectives and address specific opportunities for your business. Not all artificial intelligence tools are created equally, so selecting those with robust security and retail-specific capabilities will contribute to smoother, more streamlined operations.
Partner With an AI Expert
Retailers can enjoy a significantly easier AI integration process by working with AI experts like the team at Kopius.
We’ll help you JumpStart your success by delivering cutting-edge AI, ML, and retail technology. We understand the best practices for these solutions to enhance your business’s growth and meet your top goals. We’ll assist you in fostering tech-enabled innovation to boost digital and in-store experiences for your customers. With our help, you’ll be lightyears ahead of the competition.
JumpStart Your Retail AI Journey With Kopius
Kopius helps retail businesses use artificial intelligence and machine learning to supercharge their future. We created a program to JumpStart your data, technology, and customer success. We’ll help you take your customer shopping experiences and personalized marketing to the next level while supporting advanced data security.
With our JumpStart Retail partnership program, Kopius fast-tracks business results and enhances platform solutions. Our approach is user-centric and tailored to your unique business requirements. We will help identify your operational, customer, and team needs, ensuring your technologies align with your top priorities.
