An Interview With Chad Silverstein
The beauty of today’s AI landscape is that the entry barrier has never been lower. Small businesses can start their AI journey with just a few hundred dollars and scale as they realize tangible benefits. The key is to begin with clear business objectives rather than adopting AI for its own sake.
In today’s tech-driven world, artificial intelligence has become a key enabler of business success. But the question remains — how can businesses effectively harness AI to address their unique challenges while staying true to ethical principles? To explore this topic further, we are interviewing Eric Vaughan, CEO of IgniteTech.
Eric Vaughan is a visionary AI leader, globally sought-after speaker and pioneer of AI-driven digital clones. He spearheads IgniteTech’s AI-first transformation, reinventing products, services and workforce while shaping the future of AI in enterprise.
Thank you so much for joining us in this interview series. Before we dive into our discussion, our readers would love to “get to know you” a bit better. Can you share with us the backstory about what brought you to your specific career path in AI?
I’ve been in the technology industry for over 30 years, starting as a software developer before founding and leading three software companies. My career has always centered around interfaces and making technology accessible to people. What really brought me into AI was recognizing it as a tectonic shift — comparable to the invention of the internet, the web browser, the personal computer and the iPhone.
When ChatGPT was released in late 2022, I had that “iPhone moment” revelation that Jensen Huang, NVIDIA’s CEO, talked about. What struck me wasn’t just the technology itself, but how people outside the tech industry were suddenly engaging with it. When friends and family who weren’t technologists started asking me about ChatGPT, I realized something fundamental had changed — we’d finally created an interface that democratized access to AI’s power through natural language.
That’s when I knew we had to transform our companies completely. At IgniteTech, we’re an enterprise software company with over 40 products serving thousands of customers worldwide. I saw AI not just as another feature to add, but as an existential imperative that would redefine how software works. So, in early 2023, we initiated a dramatic transformation journey to become an AI-first organization — essentially creating an AI startup inside our 30-year-old enterprise software company.
Can you share the most interesting story that happened to you since you started working with artificial intelligence?
The most fascinating moment came at an AI conference in Las Vegas in March 2023. I had just announced our product “Jive Personas,” which uses AI to clone subject matter experts to make their knowledge more accessible. After my presentation, a gentleman rushed up to me in the hallway, incredibly excited, saying, “When can I get it? I need that now!”
He explained he had over 10,000 entry-level workers constantly asking the same basic questions about clocking in, time cards and other repetitive matters. When I mentioned he’d need to use our Jive platform, he said, “That’s fine, I don’t care. I’ll throw out SharePoint if I can get this.”
That was a profound moment — in my entire career running software companies, I’d never heard someone say they’d happily abandon a competitor’s product to get ours. It revealed something crucial: we weren’t just making incremental improvements; we were solving a universal human problem. Everyone wants to multiply their expertise and reduce repetitive interactions.
This encounter made us pivot our entire strategy. We realized it wasn’t about embedding AI into our existing Jive product; it was about creating a standalone solution (now called “MyPersonas”) that could work with any knowledge system. That single hallway conversation completely reshaped our vision and led to what’s now one of our most revolutionary products.
You are a successful leader in the AI space. Which three character traits do you think were most instrumental to your success? Can you please share a story or example for each?
Belief in possibility: I’ve found that the fundamental difference between those who succeed with AI and those who don’t is belief. The successful AI innovators simply believe it can work. At IgniteTech, I tell my team, “I know AI can’t do everything, but I want it to try everything, and I believe it can.” This reminds me of a scene from Star Wars where Luke Skywalker tries to lift his X-wing spaceship from the swamp using the Force. When he fails, he says to Yoda, “I don’t believe it,” and Yoda responds, “That is why you fail.” The message is clear — belief is the foundation of achievement. When we were developing MyPersonas, skeptics said, “AI can’t truly represent a human expert.” Instead of accepting limitations, we asked, “How can we make it work?” That belief-driven approach led us to create a patent-pending system that connects AI personas with their human counterparts when needed.
Courage to make difficult cultural changes: Transforming an organization requires tough decisions. When we committed to becoming AI-first, we first invested extraordinary effort in bringing everyone along. We reimagined our all-hands meetings as AI education sessions. We provided every employee with a $200 stipend for AI tools and ChatGPT+ subscriptions. We brought in outside experts like Ethan Mollick from Wharton to conduct workshops. We instituted “AI Mondays,” where 20% of our payroll — our entire workforce — spent every Monday focused exclusively on AI learning and development.
Despite these investments in education and culture, we knew we needed everyone rowing in the same direction. In Q3 2023, we created a month-long program measuring AI engagement — not skill or aptitude, just willingness to try. We awarded $2,500 bonuses to top performers but made it clear that those who wouldn’t engage would exit the company. We weren’t looking for experts; we were looking for belief and effort. Over five quarters, despite all our investment in the existing team, we ended up replacing almost 80% of our workforce — not reducing headcount, but bringing in people who embraced our AI-first vision. It wasn’t easy, but that cultural transformation, after exhausting every effort to bring people along, was essential to our innovation speed. We’ve gone from concept to market-ready products in timeframes that would have been impossible before.
Obsession with human-AI synergy: I fundamentally reject the “humans versus AI” narrative. Throughout history, we’ve feared new technologies — from bronze tools to the internet — only to eventually harness them for benefit. I believe in what Ethan Mollick calls the “centaur model,” where humans and AI work together, each handling what they do best. This philosophy shaped our MyPersonas technology, which doesn’t just create AI replicas of experts but maintains the connection to the human when needed. When the AI can’t answer a question, it contacts the real person through our mobile app. The human can provide the answer, and the system gets smarter for next time. This vision of human-AI collaboration — not replacement — has guided our most successful innovations.
Let’s jump to the primary focus of our interview. Can you share a specific example of how you or your organization used AI to solve a major business challenge? What was the problem, and how did AI help address it?
One of our most significant challenges was effective customer communication at scale. With thousands of customers globally, many of whom do not speak English as their first language, we faced two critical problems: how to provide personalized engagement to each customer and how to communicate effectively across language barriers.
Our traditional email communications were one-size-fits-all, typically in English, and lacked the contextual understanding needed for truly effective customer engagement. This resulted in lower response rates, miscommunications and missed opportunities to address customer needs proactively.
We approached this challenge by first developing an internal AI email system that could understand customer context, respond in their native language and maintain appropriate brand voice and technical accuracy. This began as an internal tool but evolved into what is now our Eloquens AI platform.
Eloquens AI leverages our patent-pending AI-enabled data structures to ensure communications are not only personalized but factually grounded in our knowledge base. The system can communicate fluently in over 160 languages without translation — it actually “thinks” in the customer’s language, maintaining cultural nuances and technical terminology that often gets lost in translation.
What makes Eloquens truly powerful is its human-AI orchestration. When the system encounters a situation requiring human judgment, it seamlessly escalates to the appropriate team member while capturing that interaction to improve future communications. It’s more than automating emails — it’s amplifying human expertise.
The results have been transformative. We’ve achieved a 70% reduction in response time for customer inquiries, an 85% decrease in manual email processing and dramatically improved engagement with our non-English speaking customers. Customer satisfaction scores have increased across all regions, with the most significant improvements in areas where English is not widely spoken.
What’s particularly interesting is that we didn’t reduce our customer success team size — we redeployed them to focus on building deeper relationships and addressing complex customer needs rather than routine communications. The system doesn’t replace the human touch; it extends it to places where it couldn’t reach before.
This initiative showcases the power of the “centaur model” in action — AI handles high-volume, pattern-based communications while humans focus on relationship-building and complex problem-solving where they add the most value.
What are some of the common misconceptions you’ve encountered about using AI in business? How do you address those misconceptions?
The most pervasive misconception is that “AI is coming for our jobs.” This fear-based narrative has been around for decades, reinforced by pop culture from “2001: A Space Odyssey” to “The Terminator.” I address this directly by reframing the conversation: “AI won’t replace people, but people who use AI will replace people who don’t.”
Another misconception is believing AI must be 100% perfect to be valuable. I often encounter technical people who say, “AI can’t do that” or “AI will hallucinate.” My response is: “Does it need to be perfect or just better than what we’re doing now?” If AI handles 60% of a task accurately, that’s an enormous gain. At IgniteTech, we’ve embraced the idea that we can start with partial automation and improve over time. Perfect shouldn’t be the enemy of better.
There’s also confusion about AI being strictly a technology initiative. Many companies create an “AI committee” or relegate it to IT, failing to recognize that it’s fundamentally a cultural and business transformation. I’ve addressed this by making AI adoption a CEO-driven priority, not a siloed project. We instituted “AI Mondays,” where our entire company spends each Monday focused exclusively on AI learning and development — that’s 20% of our workweek dedicated to AI transformation. This sends a clear message that AI is central to our business strategy, not just a technical add-on.
Finally, many businesses misconceive AI as primarily about cost-cutting. I reframe this as value creation. AI can certainly reduce costs, but its greatest potential is in creating new capabilities and customer experiences that weren’t possible before. We regularly share examples of AI innovations that deliver new value rather than just automating existing processes. This shifts the conversation from “what will we eliminate?” to “What can we create?”
In your opinion, what is the most significant way AI can make a positive impact on businesses today?
The most profound impact AI offers businesses today is democratizing expertise. This is about making specialized knowledge and capabilities accessible throughout organizations in ways previously impossible.
Consider what happens in most businesses: expertise becomes concentrated in a handful of people who become bottlenecks. Everyone needs access to the legal expert, the technical specialist or the star salesperson, but these people have limited time and bandwidth. Critical decisions get delayed, opportunities are missed and junior team members lack guidance when they need it most.
AI is changing this paradigm by allowing organizations to capture, scale and distribute expertise. With technologies like our MyPersonas AI SME-cloning software, a subject matter expert’s knowledge can be made available 24/7 to anyone who needs it. When someone has a question about legal compliance, product specifications or sales techniques, they don’t have to wait for the one expert who knows the answer — they can get immediate guidance based on that expert’s knowledge and experience.
What makes this truly revolutionary is that it’s not an either/or proposition. When the AI encounters something it doesn’t know, our system allows it to contact the actual human expert. The expert can provide an answer once, and the system gets smarter for everyone. This creates a virtuous cycle where expertise becomes more accessible while experts are freed to focus on novel challenges.
The business impact is transformative. Decision-making accelerates across the organization. New employees get up to speed faster. Expertise isn’t lost when someone leaves. And perhaps most importantly, your top performers are liberated from answering the same questions repeatedly, allowing them to tackle more complex challenges that drive innovation.
This democratization of expertise is the most significant business impact because it addresses a universal problem that affects organizations of all sizes across every industry. It’s improving efficiency — fundamentally changing how knowledge flows through businesses.
Ok, let’s dive deeper. Based on your experience and research, can you please share “5 Ways AI Can Solve Complex Business Problems”? These can be strategies, insights, or tools that companies can use to make the most of AI in addressing their challenges. If possible, please share examples or stories for each.
1. Transform User Interfaces to Eliminate Search and Navigation Friction
Traditional software interfaces force users to navigate complex menus or search through haystacks of information to find what they need. AI can fundamentally reimagine these interactions by providing exactly what users want — the needle, not the haystack.
We’ve seen this firsthand. In July 2024, we partnered with Chatsimple to completely reinvent our corporate website, moving from traditional navigation to an AI-driven conversational interface at ignitetech.ai. Instead of forcing visitors to click through menus and pages, they simply ask for what they want and get direct answers.
The results were immediate: engagement increased 400%, and the average time visitors spent interacting with our content nearly tripled. More importantly, the quality of interactions improved dramatically. Visitors were getting precisely what they needed rather than approximate matches from a search function.
This approach works across all customer-facing interfaces. For businesses looking to implement this strategy: start by identifying your most complex customer journeys, analyze the questions users are really trying to answer and build conversational AI that delivers direct solutions rather than forcing navigation.
2. Scale Expertise Through AI-Powered Digital Personas
Every organization has critical knowledge bottlenecks — subject matter experts who are constantly bombarded with the same questions, creating dependency and frustration on all sides.
Our solution to this was developing MyPersonas, which creates AI-powered digital twins of your organization’s experts. These aren’t just chatbots; they’re personalized extensions that embody an individual’s knowledge, appearance and communication style.
For businesses implementing this strategy: identify your key knowledge bottlenecks, document the most frequently asked questions these experts handle and consider solutions that not only automate responses but maintain the connection to human expertise when needed.
3. Drive Cultural Transformation Through Structured AI Engagement
AI adoption often fails because companies approach it as a technology initiative rather than a cultural shift. To succeed, businesses must systematically reshape how their teams think about and engage with AI.
With “AI Mondays,” 20% of our total workweek was exclusively dedicated to AI learning, experimentation and development for an entire quarter. Everyone from finance to engineering to customer support spends each Monday focused solely on AI initiatives relevant to their role.
This structured approach delivered surprising results. In just three months, we saw a 300% increase in AI-driven process improvements across departments. Our finance team, for instance, reduced quarterly closing processes from five days to less than 48 hours by reimagining their workflows with AI.
For businesses implementing this strategy: dedicate protected time for AI exploration, create cross-functional teams to break down silos, tie AI initiatives to measurable business outcomes and ensure executives visibly participate in the process.
4. Eliminate Interface Barriers with Multimodal AI
Complex business problems often stem from the friction between humans and technology interfaces. Multimodal AI — which combines text, voice, video and image understanding — can eliminate these barriers entirely.
We incorporated multimodal capabilities into our MyPersonas technology, allowing users to interact through whatever medium is most natural — typing questions, speaking conversationally or uploading images of problems they’re trying to solve.
A manufacturing client implemented this approach for equipment maintenance. Technicians now simply show their mobile device an unfamiliar part, and the system identifies it, provides maintenance history and offers visual repair guidance — all through natural conversation rather than complex manual navigation.
For businesses implementing this strategy: identify processes where interface friction creates bottlenecks, prioritize natural interaction methods appropriate to your environment (voice may be better in some contexts, visual in others) and design for inclusive accessibility across user technical capabilities.
5. Bridge Data Silos with AI-Enabled Data Structures
Most organizations struggle with fragmented information across disconnected systems — customer data in the CRM, product information in the ERP, support history in the ticketing system and tribal knowledge in employees’ heads.
We’ve developed what we call “AI-PIs” (vs. APIs) — AI-enabled data structures that normalize information from disparate sources, creating a unified knowledge layer that AI systems can reason across.
For a financial services client, this approach transformed customer support. Previously, representatives needed to access seven different systems to resolve complex issues. Now, their AI assistant integrates all relevant information in real-time, cutting resolution time by 68% while improving accuracy.
For businesses implementing this strategy: map your critical data flows, identify integration points that would deliver the most impact and design AI systems that act as connective tissue across your information landscape rather than creating yet another silo.
How can smaller businesses or startups, with limited budgets, begin to integrate AI into their operations effectively?
The good news for smaller businesses is that AI democratization is happening at an unprecedented pace. You don’t need massive budgets or specialized teams to start reaping benefits. Here’s my practical advice based on working with businesses of all sizes:
Start with “low-hanging fruit” processes that are high-volume and rule-based. Customer email responses, scheduling, data categorization and basic content creation are ideal entry points. These don’t require custom AI development — they can leverage existing tools with minimal configuration.
Take advantage of the “API economy.” Most small businesses are already using platforms like Salesforce, Microsoft 365 or Google Workspace that now have embedded AI capabilities. Before investing in standalone solutions, fully explore what’s already available in your existing tools. Microsoft’s Copilot, for instance, offers significant productivity gains with no additional infrastructure needed.
Remember that AI adoption is more about process than technology. The most common mistake I see is when small businesses purchase an AI tool without redesigning their workflows around it. Start by mapping your current processes, identifying friction points, and then determine how AI can address those specific challenges.
For businesses with extremely limited budgets, consider a “personal AI first” approach. Have team members experiment with tools like ChatGPT Plus, Claude or Perplexity to augment their individual work. This builds AI literacy within your team at minimal cost ($20–30 per person monthly). Once you see what’s possible, you can scale the most impactful applications.
Finally, don’t underestimate the power of community. There are thriving online communities where small businesses share AI prompts, workflows and implementation strategies. These collective resources can dramatically reduce your learning curve and help you avoid costly mistakes.
The beauty of today’s AI landscape is that the entry barrier has never been lower. Small businesses can start their AI journey with just a few hundred dollars and scale as they realize tangible benefits. The key is to begin with clear business objectives rather than adopting AI for its own sake.
What advice would you give to business leaders who are hesitant to adopt AI because of fear, misconceptions, or lack of understanding?
First, recognize that hesitation is natural — every technological revolution has faced initial resistance. But also understand that AI isn’t just another tech trend; it’s a fundamental shift comparable to the internet or smartphones. The question isn’t whether AI will transform your industry but whether you’ll be among those leading that transformation or scrambling to catch up.
I advise skeptical leaders to start with education — not technical education, but strategic understanding. Read case studies from your industry, attend executive-focused AI events (not developer conferences) and connect with peers who are further along in their AI journey. The goal isn’t to become an AI expert but to understand its business implications specific to your context.
Next, adopt what I call “controlled experimentation.” Identify a contained, low-risk area of your business where AI could add value. Define clear success metrics, set a reasonable timeframe (90 days works well) and commit resources to a proper pilot. This approach manages risk while providing concrete evidence of impact.
Address fear directly by reframing the conversation from replacement to augmentation. Throughout history, new technologies have ultimately created more opportunities than they eliminated. In our experience transforming IgniteTech, we didn’t reduce our workforce — we redeployed people to higher-value activities as AI handled routine tasks. Share this perspective with your team from the beginning.
Perhaps most importantly, recognize that AI adoption is fundamentally a leadership challenge, not a technical one. Your visible commitment sets the tone. I re-branded myself as “the Gen AI CEO” and made our AI transformation the central focus of everything we do. This signaled to everyone that this wasn’t just another initiative but our strategic direction.
Finally, consider the competitive implications of inaction. In early 2023, I told our company that AI represented an existential challenge — not because AI would replace us, but because competitors embracing AI would. Business leaders sometimes focus on the risks of adoption while underestimating the risks of standing still. The market rarely rewards caution when paradigms are shifting.
In your opinion, how will AI continue to shape the business world over the next 5–10 years? Are there any trends or emerging innovations you’re particularly excited about?
Making predictions about AI beyond the next 12–18 months is challenging given the pace of change — a point I often make when speaking at conferences. However, I see several trajectories that will reshape business fundamentally.
The most significant shift will be from general-purpose AI to domain-specialized AI that deeply understands specific industries and business contexts. We’re already seeing early examples with legal AI assistants that understand case law or healthcare AI that comprehends medical terminology. These systems will become so specialized that they’ll redefine professional expertise in ways we’re just beginning to grasp.
I’m particularly excited about the evolution of human-AI interfaces. Today’s text and voice interfaces are just the beginning. We’re moving toward ambient AI that understands context, anticipates needs and integrates seamlessly into our work environments. The future won’t be about “using AI tools” — AI will be an invisible layer augmenting every business process, just as the internet evolved from something we “logged into” to an omnipresent utility.
The democratization of AI development will accelerate dramatically. We’re already seeing tools that allow non-technical users to create sophisticated AI applications. This will unleash innovation from the edges of organizations rather than centralized tech teams. The next breakthrough app or process might come from your marketing team or customer service department rather than IT.
On the business model front, AI will drive the rise of “personalization at scale” across industries. The historical trade-off between customization and efficiency will disappear. We’ll see mass-customized products, individualized service experiences and personalized pricing — all delivered with greater efficiency than today’s standardized approaches.
Perhaps most profoundly, AI will reshape organizational structures. The traditional hierarchy optimized for information flow up and decisions flowing down will become obsolete when AI can analyze patterns across the entire organization instantly. We’ll see flatter, more dynamic structures where decision authority shifts based on expertise and context rather than position.
These changes won’t happen uniformly across all businesses or industries. The leaders who win will be those who view AI not as a technology to implement but as a lens through which to reimagine their entire business. Those who merely “add AI” to existing processes will find themselves outpaced by competitors who fundamentally reinvent what’s possible.
How do you think the use of AI to solve business problems influences relationships with customers, employees, and the broader community?
AI is fundamentally reshaping relationships across all these dimensions, but not in the dystopian way many feared. We’re discovering that when implemented thoughtfully, AI can actually make business interactions more human, not less.
With customers, AI is enabling a return to personalization at scale. For decades, business growth meant standardization and loss of personal connection. When we launched MyPersonas, we discovered customers weren’t just excited about efficiency — they were excited about having consistent access to expertise that previously required waiting for the “right person.” One healthcare customer reported that patient satisfaction increased by 38% when they implemented AI personas of their specialists to provide consistent, accurate information between appointments. The technology created more touchpoints for human-like interaction, even though some of those interactions were AI-powered.
For employees, AI is redefining the relationship between people and their work. At IgniteTech, we’ve seen a dramatic shift in job satisfaction as AI has taken over repetitive tasks. Our support engineers previously spent 70% of their time on routine tickets and 30% on complex, interesting problems. Today, that ratio has flipped — they’re primarily engaged in challenging work while AI handles the routine. This hasn’t eliminated jobs; it’s elevated them. We’re seeing increased employee retention among teams that have successfully integrated AI into their workflows.
Within the broader community, AI is beginning to address inclusivity challenges that have persisted for generations. The ability of systems like MyPersonas to communicate fluently in over 160 languages improves efficiency and creates access for people previously marginalized by language barriers. A government agency using our technology reported that engagement from non-English-speaking communities increased fivefold when citizens could interact in their native languages with the same level of service as English speakers.
Perhaps most importantly, AI is shifting power dynamics in all these relationships. When expertise is democratized through AI, the traditional gatekeepers of knowledge lose their monopoly. Customers become more informed, employees at all levels gain access to insights previously reserved for executives and communities can engage with organizations on more equal footing.
The organizations thriving in this new landscape are those that embrace this redistribution of power rather than resisting it. They recognize that AI doesn’t replace relationships — it transforms them by removing friction and creating space for more meaningful human connection.
You are a person of great influence. If you could start a movement that would bring the most amount of good to the most amount of people through AI, what would that be? You never know what your idea can trigger. 🙂
I would launch what I call the “AI Rising Tide” movement, focused on ensuring AI becomes the great equalizer it has the potential to be, rather than another technology that primarily benefits those already advantaged.
The core principle would be simple but powerful: AI should lift all boats, not just luxury yachts. Studies already show that when lower-skilled workers are given access to AI tools, they experience disproportionately larger productivity gains than highly skilled workers — often closing performance gaps by 40% or more. This suggests AI could be the most powerful force for economic opportunity in generations, but only if we deliberately design for inclusivity.
The movement would operate on three fronts:
First, we’d establish “AI Community Centers” in underserved regions, both in developed and developing countries. These physical hubs would provide free access to AI tools, training and mentorship, focusing on practical applications that create immediate economic value — helping small farmers optimize crop yields, enabling local craftspeople to reach global markets or supporting community healthcare workers with diagnostic assistance.
Second, we’d create an open-source “AI Curriculum for All” designed to work across diverse educational levels and cultural contexts. This wouldn’t be focused on creating AI engineers — though that pathway would exist — but on teaching everyone how to effectively collaborate with AI across every profession and trade. The curriculum would be translated into hundreds of languages and adaptable to contexts from formal education to community workshops.
Third, we’d launch a global “AI Public Utilities” initiative, developing and maintaining a collection of industrial-strength AI tools for critical social needs — education, healthcare, agriculture and small business support — that would remain permanently free and accessible to anyone. These wouldn’t be stripped-down versions of commercial tools but fully-featured systems optimized for impact rather than profit.
What makes this movement different from typical tech philanthropy is that it would embed AI democratization directly into the business models of participating companies. At IgniteTech, we already donate software to nonprofits, but the AI Rising Tide movement would go further — companies would commit to making their AI innovations available to underserved communities through structured programs, not just occasional charity.
The opportunity is extraordinary: we stand at a unique moment where AI could either widen inequality dramatically or become the greatest leveling force in economic history. The choice is ours, and I believe business leaders have a profound responsibility to ensure we choose wisely.
How can our readers further follow you online?
I’m active on several platforms where I regularly share insights about AI transformation, leadership and the future of business:
- LinkedIn: Eric Vaughan
- Twitter/X: @TheGenAICEO
- Our corporate blog at IgniteTech.ai/blog
I also speak frequently at industry events and conferences focused on AI transformation. You can find my upcoming speaking engagements on the IgniteTech website.
For those specifically interested in our AI innovations like MyPersonas, visit MyPersonas.ai for the latest updates and case studies.
I’m passionate about helping organizations of all sizes navigate the AI revolution, so I welcome connections from readers who have questions or want to share their own AI transformation stories!
This was great. Thank you so much for the time you spent sharing with us.
Thank you for this opportunity. The conversation around AI is often dominated by either technical minutiae or dystopian fears, so I appreciate forums like Authority Magazine that focus on the practical human impact of these technologies. AI represents a profound opportunity to reshape how we work, communicate and solve problems — but only if we approach it with the right mindset and values. I’m grateful to share my perspective and hope it helps readers navigate their own AI journeys more confidently.
About the Interviewer: Chad Silverstein is a seasoned entrepreneur with 25+ years of experience as a Founder and CEO. While attending Ohio State University, he launched his first company, Choice Recovery, Inc., a nationally recognized healthcare collection agency — twice ranked the #1 workplace in Ohio. In 2013, he founded [re]start, helping thousands of people find meaningful career opportunities. After selling both companies, Chad shifted his focus to his true passion — leadership. Today, he coaches founders and CEOs at Built to Lead, advises Authority Magazine’s Thought Leader Incubator.
Eric Vaughan Of IgniteTech On How Artificial Intelligence Can Solve Business Problems was originally published in Authority Magazine on Medium, where people are continuing the conversation by highlighting and responding to this story.