How enterprises can successfully adopt generative AI
At Creed, we believe in building technology that works beautifully. This means combining creativity with disciplined process and execution. That same philosophy is guiding how we’re integrating AI into our business.
In just about every industry, the buzz around AI is loud. At Creed, we’re leaning into AI with intention, guardrails, and most importantly, with purpose. Here’s a look at how we’re using AI not to replace people, but to elevate them, while unlocking real business efficiencies in the process.
Generative AI —tools that can create text, images, code, and more based on prompts—is changing the way businesses think about productivity, creativity, and automation. Whether it’s streamlining content creation, enhancing customer service, or speeding up data analysis, GenAI offers powerful capabilities that can significantly improve operations and decision-making. But harnessing that potential isn’t just about buying software or spinning up a chatbot. It requires a strategic approach, thoughtful planning, and coordination across business and technology teams.
At Creed Interactive, we’ve partnered with enterprises across industries who are eager to capitalize on GenAI. We’ve seen what works—and more importantly, what actually delivers business value in production. This guide is designed to help business executives, IT leaders, and project managers chart a clear, practical path for adopting GenAI, from building the right pilot program to scaling across the organization.
Start with a real-world problem, not a technology demo
One of the most common challenges in AI adoption is starting from the wrong end—choosing a tool first and trying to find a use for it later. Instead, successful teams begin by identifying real pain points in the business. These are often manual, time-consuming, or repetitive tasks that frustrate employees and slow down operations.
For example, are teams spending hours every week creating summaries, responding to customer emails, or compiling routine reports? Are developers slowed down by repetitive code review tasks or documentation burdens? These are often ideal opportunities to introduce GenAI, because they’re well-defined, measurable, and low-risk.
Start small and think practical. Focus on areas where AI can reduce time spent, improve output consistency, or allow staff to focus on higher-value work. From there, you can build a use case that clearly aligns with a business outcome, like reducing turnaround times, increasing customer satisfaction, or lowering operational costs.
Design a focused pilot that’s built to learn and scale
Pilot programs are a smart entry point for most organizations, but they need structure to succeed. The best pilots are not open-ended experiments, they are focused, goal-oriented projects that test a specific use case with a well-defined audience. They are designed not just to explore, but to learn what works and what doesn’t in your environment.
Let’s say your goal is to use GenAI to help customer support teams respond to tickets faster. Your pilot could involve a single support team, using a generative assistant to draft replies based on prior case history and documentation. Success criteria might include reduced response time, improved consistency, or lower escalation rates. By keeping the scope narrow and the objectives clear, you’ll be able to measure real outcomes and identify any technical or organizational hurdles.
Also, don’t wait until the pilot is over to think about what’s next. Design your pilot with the future in mind by building it using tools, data access, and security models that can scale if the pilot is successful.
Involve the right people early and often
One major success factor in GenAI adoption is getting the right people at the table from the start. That means going beyond just IT or innovation teams. Business stakeholders, legal and compliance, operations, design, and security should all have a seat during planning and execution.
Cross-functional collaboration helps you avoid surprises down the road. Legal can flag privacy risks before sensitive data is exposed. Designers can create interfaces that make the tools more intuitive. Ops leaders can spot workflow conflicts or identify process automation opportunities. And security can ensure that your use of GenAI meets regulatory requirements from day one.
When these voices are involved early, pilots move faster, adoption is smoother, and solutions are better aligned with how people actually work.
Get your data in shape before the AI arrives
Generative AI is only as good as the data it has access to. Whether you’re using AI to generate reports, summarize internal documents, or assist with decision-making, the underlying data needs to be accurate, accessible, and relevant. Too often, enterprises dive into AI without considering data readiness, only to find that the tools can’t deliver meaningful results.
Before launching your pilot, identify the data sources the GenAI solution will need. Is that internal documentation, historical tickets, emails, or databases? Can that data be securely accessed? Is it up to date and free of duplication or noise? If not, consider allocating time to data preparation before expecting the tool to perform at a high level.
For advanced use cases, look into retrieval-augmented generation (RAG) frameworks, which combine GenAI’s creativity with search and contextual retrieval from internal content libraries. This allows the AI to generate responses based on your own proprietary knowledge, not just what it was trained on publicly.
Prioritize security, governance, and compliance from the start
Security and governance should never be an afterthought in GenAI adoption. Many organizations are rightly concerned about how AI might introduce risk, whether it’s through misuse, hallucinated content, or exposure of confidential information.
To protect your business and your customers, you’ll need a clear AI governance framework. This includes setting usage policies, determining what kinds of data can be shared with AI tools, and defining when human review is required. It also means choosing the right models and deployment environments. For example, some organizations may choose to run GenAI models in private environments or use vendor tools that offer enterprise-grade security and auditability.
Most importantly, involve compliance and legal teams early. By anticipating regulatory needs and privacy issues from the outset, you can design pilots and scale-out plans that are compliant by design, not just compliant after the fact.
Make it easy for teams to use and trust the tools
Even the most advanced GenAI tool will fall flat if employees don’t understand how to use it—or don’t trust what it produces. That’s why user experience (UX) and change management are critical.
Start by designing interfaces that are clear, guided, and forgiving. For many users, typing prompts into a text box is a new interaction model. Offer prebuilt prompt templates, tooltips, and guardrails to guide them. Clearly explain what the AI is doing, how it reaches its outputs, and where human review is needed.
Also, don’t assume users will adopt tools on their own. Create training resources, host onboarding sessions, and share real success stories from inside the company. Celebrate wins and gather feedback early and often to improve the tools and increase confidence.
Scale with intention
Once a pilot has shown promise, it’s time to think about how to expand, without losing control or momentum. Scaling GenAI solutions isn’t just about flipping a switch. It requires planning, standardization, and continuous improvement.
Start by identifying additional departments or workflows that could benefit from the pilot’s success. Use the lessons learned—what worked, what needed tweaking—as a playbook for the next phase. Build shared infrastructure and governance processes that can support multiple use cases. And continue to invest in cross-functional teams to support adoption, training, and evaluation.
Remember, successful GenAI adoption is a journey, not a single rollout. Prioritize agility and iteration, and treat GenAI as a capability your organization is growing over time, not just a tool it’s buying once.
Checklist for Your GenAI Pilot
Use this quick-reference list to make sure your AI pilot sets the stage for real-world results:
□ Identify a real, measurable problem – Focus on manual or repetitive tasks that slow teams down. Don’t start with the tech.
□ Define clear success metrics – What does success look like? Set specific outcomes like reduced response time or higher accuracy.
□ Assemble a cross-functional team – Involve business, IT, legal, design, and ops early to ensure alignment and adoption.
□ Prep your data sources – Make sure the AI has access to clean, relevant data. Consider retrieval-augmented generation (RAG) for deeper context.
□ Plan for governance and compliance – Establish usage policies, data access rules, and review processes from the start.
□ Design a usable, trusted experience – Help users understand how the tool works and how to use it confidently. Include training and support.
□ Build with scale in mind – Choose tools and workflows that can grow with you. Think beyond the pilot from day one.
Final thoughts
Generative AI has the power to reshape how your business operates, but it takes more than excitement to unlock that value. With the right approach, enterprises can move from curiosity to clarity, from pilot to production, and from experimentation to measurable impact.
Start by solving a real problem. Involve your teams. Prepare your data. Respect governance. Design for usability. And most importantly, think beyond the pilot, because the real value of GenAI begins when it becomes part of how your organization works every day.
At Creed, we help organizations like yours bring GenAI into the real world through well-designed pilots, scalable infrastructure, and people-centered experiences that stick.
If you’re ready to move beyond experimentation and build a GenAI solution that delivers real results, we’d love to help. Schedule a free GenAI strategy session with our team to explore practical next steps tailored to your business.