And here we are again! After a few months' break, we're back with another Growth Talk.

Meet Reginald (Reggie) Manning, Co-Founder and CEO of Vista Data, a Memphis-based company bringing AI-powered training to the people who need it most, educators, workforce teams, and communities that often get left behind when new tech shows up.

Reggie's path to AI didn't start in Silicon Valley. It started in education, running a tutoring franchise, leading workforce programs, growing a charter school network's revenue from $4M to $20M as COO, and managing a $790M product portfolio at a Fortune 100 company. All of that before he decided to build something of his own.

Vista Data launched in 2023 with a simple idea: AI shouldn't be something only big companies and technical teams get to use. Since then, Reggie and his team have been building training programs, deploying one of the first AI-powered tutors in a public middle school, and working to make AI education accessible for everyone.

Let's hear his story.

1. Always starting simple. What does growth mean to you?

Meaningful progress that acknowledges where you are and where you plan to go.

2. For people who haven't heard of Vista Data,  what do you do, who do you do it for, and how did it all start?

We train people from non-technical backgrounds how to leverage machines (AI) to “bend” time and solve everyday problems. We target the current and future workforce to fine-tune existing skills and apply them to future workforce needs. It started with curiosity about how to leverage AI to help students close learning gaps caused by the COVID-19 pandemic.

3. You've led teams at big organizations and now you're running your own startup. Which is harder, and why?

They both have their challenges. Large companies have layers, processes, and a slower cadence, more like a cruise ship. They typically have more resources to do more and go farther. In contrast, startups are more challenging. You can move quickly with little restraint, but you’re typically short on fuel (resources), and a wrong turn or diversion can be costly. I respect the discipline and process of a large company (which at one point was a startup) and believe you can leverage that experience to create something special. For a business creative like myself, startups are both more challenging and more rewarding.

4. You work with schools, government, healthcare, these are sectors that move slowly and have a lot of rules. How do you bring something as new as AI into organizations that don't move fast?  

There is incredible opportunity for transformation and intentional adoption in established sectors. It's less about speed and more about aligning technology with the evolving baseline of real-world needs. We focus on showing how AI serves as a powerful multiplier for the impactful work these organizations are already doing. By taking a proactive approach centered on "how these tools can amplify success," we empower leaders to achieve better, faster, and more impactful outcomes.

5. There's a lot of fear around AI right now, people worried about jobs, about kids using it wrong, about it replacing teachers. What do you say to that?

In many instances, a healthy amount of fear is good. We should not go “all in” blindly into anything. However, in many cases, we fear what we don't understand. With any innovation, it’s good to be both curious and cautious. AI has many capabilities, but fundamentally it mimics humans. Just as humans are not perfect, neither is AI, which is even more reason to keep a “human in the loop.” I believe there are aspects of human interaction that are necessary and hard to replace. In terms of AI replacing jobs, it will replace some. More importantly,it is my belief that humans who are proficient with AI tools will replace those who aren't.

6. AI training is everywhere now, courses, bootcamps, certifications. A lot of it feels generic. What makes good AI training versus bad AI training, and who's being left out of the conversation?

It can become overwhelming; there is a lot of noise in the market and sometimes it is challenging to discern good from bad. You can literally learn almost anything anywhere. Training is only as good as the practical application of what you have learned. Your “use case” should facilitate the tool selection. The non-technical/digital learner is the forgotten one. AI sounds scary and technical, but the main programming language is “natural language.” If you can communicate with humans, you can direct that communication to machines with the right guidance, strategy, and outcomes.

7. A lot of companies say they want to "adopt AI" but have no idea where to start. What's the first thing you tell them?

I believe before you adopt AI, you must first assess what your challenges are and gain a better understanding of areas where improvements will actually move the needle. Once you have a proper understanding, it becomes much easier and makes more sense to implement strategies and tools that accomplish your specific goals. Identify a problem first, and then add the technology or application. Don't start with technology looking for a problem that hasn't been identified yet.

8. AI moves so fast, new models, new tools, new everything every week. How do you personally keep up? What does your learning routine look like?

I draw from various sources: from social media, videos, and podcasts to newsletters and any information that is remotely relevant. I also like to draw inspiration from non-related materials with a curiosity about what could be. I enjoy drawing from a variety of sources and researching problems that AI tools could solve. I often take an artistic, creative approach by exploring different ideas and blending them into something original. 

9. What's the biggest mistake you've made building Vista Data so far, and what did it teach you? And where is Vista Data headed in the next two or three years?

I view every experience as a valuable learning opportunity and a part of our continuous growth cycles, evaluating all outputs to continuously refine our approach. Agility in responding to fast-changing models and tools is an exciting driver for us, and each phase offers new insights to accelerate our journey. In the next 2 to 3 years, Vista Data will continue to expand its reach and impact, enabling growth across industries and domains. As technology evolves, our commitment to staying at the pulse of change ensures we will be at the forefront of unlocking even greater opportunities across workforce development, education and human potential.

10. Last one. What advice would you give to someone from a non-technical background who wants to get into AI?

‍Identify the way you learn best, whether it's visual, auditory, or hands-on, and then find channels of information that feed your exploration. There are so many opportunities to learn; just fine-tune the best learning method for you and see where it takes you.

‍

‍