AI Innovation in Action: Lessons for Leaders on Strategy, Risk, and Building for the Future

AI is no longer a distant promise; it’s a present-day reality transforming industries and redefining how businesses operate. Yet for leaders, the challenge lies not in adopting AI itself but in strategically implementing it to deliver measurable business value, reduce risk, and create enduring solutions.

At the recent Ohio AI Summit, a panel featuring industry pioneers, including Nate Sowder, Fifth Third, Nima Gard (Director of AI, Path Robotics), Lynn Sautter Beal (VP of Implementation and Success, Upstart), and Ryan Lunka (Co-Founder and CEO, Doohickey AI), shared valuable insights on how they’re turning AI potential into actionable strategies. Their discussion provided a roadmap for organizations to navigate the complex AI landscape while managing risks and creating lasting impact.

Whether you’re a startup founder, a corporate executive, or an innovator in a highly regulated industry, the lessons from this panel offer practical strategies for leveraging AI as a transformative tool. Here’s what you need to know.

1. Addressing Workforce Gaps with AI-Driven Automation

The growing labor shortage in industries like manufacturing has become a significant barrier to productivity and growth. Nima Gard explained how Path Robotics is addressing this challenge using AI to enable high-mix, low-volume manufacturing processes. Unlike traditional automation that relies on rigid systems, Path Robotics uses machine learning to adapt to ever-changing workflows, making automation accessible even in complex environments.

"With machine learning, we can automate tasks quickly and cost-effectively, even in industries where processes change daily." – Nima Gard

Practical Step for Leaders: If your business is grappling with labor shortages, explore how AI-powered solutions can fill the gap. For example, in manufacturing, adopting a Robot-as-a-Service (RaaS) model allows you to test AI-driven robotics without committing to large-scale deployments. Evaluate areas where repetitive tasks or high variability make traditional automation impractical and pilot AI solutions to address those gaps.

2. Building Trust in AI for Regulated Industries

In highly regulated sectors like financial services, skepticism around AI’s role and compliance risks often hinder adoption. Lynn Sautter Beal shared how Upstart tackled this challenge by creating a free AI certification program for financial professionals. The program demystifies AI’s capabilities and fosters responsible use, addressing industry concerns while encouraging broader adoption.

"We built this certification to drive a foundational understanding of AI’s power and responsible use, helping financial services professionals feel confident in adopting it." – Lynn Sautter Beal

Practical Step for Leaders: Invest in educational initiatives that bridge the knowledge gap in regulated industries. Develop training programs focused on AI ethics, governance, and real-world applications. Partner with industry associations or academic institutions to create certifications that build trust and demonstrate your organization’s commitment to responsible AI use.

3. Knowing When (and When Not) to Use AI

Ryan Lunka stressed a critical point: not every business problem requires an AI solution. The hype around AI can lead organizations to adopt the technology without a clear understanding of its value. Instead, Lunka encouraged leaders to focus on solving meaningful business problems where AI can make a transformative impact.

"This generation of AI is nascent, and it creates first-mover opportunities—but slapping a chatbot on your product isn’t enough. You need to solve real business problems with it." – Ryan Lunka

Practical Step for Leaders: Conduct a strategic audit of your business processes to identify inefficiencies or bottlenecks. Evaluate whether AI can deliver a 10x or 100x improvement in these areas, such as automating manual tasks, optimizing supply chains, or enhancing customer personalization. Avoid incremental improvements; prioritize AI initiatives that can drive transformative change.

4. Reducing Risk Through AI Trial Models

Customer skepticism is often a barrier to AI adoption, particularly for businesses with a history of failed automation projects. Path Robotics addresses this with a low-risk approach, offering trial models like Robot-as-a-Service (RaaS) and Path Foundry. These models allow customers to experience the benefits of AI-driven robotics without significant upfront investments.

"Most of our customers have tried automation before, and many failed. We make it easy to try AI-driven robotics without risk, building confidence before scaling." – Nima Gard

Practical Step for Leaders: Adopt a similar low-risk strategy by offering subscription-based models or pilot programs. This approach reduces the barrier to entry for customers, allowing them to see tangible results before committing to larger-scale implementations. Use trial periods to gather feedback, optimize solutions, and build confidence in your AI offerings.

5. Balancing Innovation with Customer-Centric Design

While AI has the potential to simplify complex tasks, poorly implemented solutions can add friction to customer interactions. The panelists emphasized the importance of holistic design that integrates AI seamlessly into the customer journey, ensuring that automation enhances rather than disrupts the experience.

"Automation is great, but if it disrupts the customer journey, it’s not enough. You have to think holistically about the entire process." – Nima Gard

Practical Step for Leaders: Before deploying AI, map out the customer journey and identify potential pain points. Use AI to address these areas while maintaining a focus on simplicity and usability. Regularly solicit feedback to refine the implementation and ensure it aligns with customer expectations.

6. Creating Companies That Outlast AI’s Hype Cycle

The panelists stressed that successful companies don’t adopt AI for the sake of it—they use it as a tool to amplify their core strengths. Ryan Lunka highlighted that the best startups focus on solving enduring problems, using AI as a superpower to enhance their offerings.

"The strongest startups aren’t building AI for AI’s sake. They’re solving real problems with AI as a superpower." – Ryan Lunka

Practical Step for Leaders: Identify your organization’s unique strengths—whether in product innovation, customer intimacy, or operational excellence—and use AI to scale these capabilities. Align AI initiatives with long-term goals, ensuring they complement rather than distract from your strategic vision.

7. Managing Third-Party Risks

For startups and established businesses alike, navigating third-party risks is a critical consideration. Lynn Sautter Beal explained how Upstart mitigates these risks by building transparent processes and aligning with best practices, such as SOC 2 compliance.

"We guide our clients on third-party risk management, using industry best practices to ensure compliance and trust." – Lynn Sautter Beal

Practical Step for Leaders: Establish clear guidelines for third-party risk management, including compliance standards and transparent reporting practices. Use recognized frameworks like SOC 2 or ISO 27001 to build trust with partners and customers. Regularly review and update these processes to address emerging risks.

8. The ROI Mindset: Beyond Cost Savings

While cost reduction is often a driver for AI adoption, the panelists urged leaders to think bigger. AI’s true value lies in its ability to unlock new revenue streams and create opportunities that wouldn’t otherwise exist.

"Cost reduction is great, but it’s capped. The real ROI comes from opening new sales channels and creating revenue opportunities." – Ryan Lunka

Practical Step for Leaders: Shift your ROI metrics from cost savings to revenue generation. Use AI to explore untapped markets, launch innovative products, or enhance customer lifetime value. Frame AI initiatives as strategic investments that drive growth, not just operational efficiencies.

A Framework for AI-Driven Success

The insights from the Ohio AI Summit demonstrate that successful AI adoption requires a thoughtful, deliberate approach. Leaders must balance innovation with risk management, customer-centric design, and long-term value creation. From reducing workforce gaps to fostering trust in regulated industries, these strategies provide a blueprint for organizations looking to turn AI concepts into reality.

Takeaway for Leaders: AI isn’t just a tool—it’s a strategic enabler that can transform how businesses operate, solve problems, and create value. Success lies in practical applications, clear objectives, and a relentless focus on delivering meaningful outcomes. Start small, learn fast, and think big—because the future of your business depends on it.

About the Author

Jason Hauer is CEO of HauerX Holdings and an Inc. 500 honoree. He partners with commercial AI tech and solutions companies to turn ambition into market leadership.