9 Transformative AI Strategies Every Leader Must Know

As AI reshapes industries at an unprecedented pace, enterprise leaders face a pivotal moment: how to harness AI to drive growth while navigating workforce readiness, equity, and sustainable innovation. The stakes are high—AI isn’t just about efficiency or automation; it’s about unlocking entirely new opportunities to solve business challenges, create competitive advantages, and position organizations for long-term success.

At the OhioX AI Conference, a recent panel discussion featuring Tonjia Coverdale, Ph.D. (SVP and Chief Strategy Officer for Operations and Technology, Associated Bank), Beena Sukumaran, Ph.D. (Dean of the College of Engineering and Computing, Miami University), and Channie Mize (General Manager, Slalom) illuminated critical strategies for enterprise leaders. These insights provide a roadmap for adopting AI as a transformative force within organizations.

1. From Infrastructure to Impact: Making AI Work for Your Organization

The conversation around AI often begins with infrastructure, building data centers, creating cloud ecosystems, and enabling basic automation. While these elements are foundational, they only scratch the surface of AI’s transformative potential. To unlock real value, leaders must shift from focusing solely on technology to prioritizing the outcomes AI can deliver for their business. This requires a strategic lens that ties AI directly to measurable goals, such as improving customer experiences, streamlining operations, or enabling new revenue streams.

"AI works for us, not the other way around. It’s a tool to amplify our mission and vision, not just to optimize processes." – Channie Mize, General Manager, Slalom

Enterprise Insight: Prioritize AI investments that tie directly to business objectives. For instance, focus on enhancing customer engagement through predictive analytics, increasing operational efficiency via process automation, or developing innovative products using AI-driven insights. Leaders should create cross-functional teams to align AI initiatives with key organizational priorities, ensuring buy-in from all stakeholders.

Key Move for Leaders: Identify two or three high-impact areas where AI can deliver measurable results within six months to a year. This could include customer experience enhancements, faster product launches, or streamlined supply chains. Use these wins to build confidence and momentum for more ambitious AI projects.

2. Building an AI-Ready Workforce

AI’s success in any organization is determined as much by the people who use it as by the technology itself. Yet, workforce readiness often lags behind technology adoption. For AI to deliver its full potential, leaders must focus on preparing employees with the skills, confidence, and mindset needed to integrate AI into their work. Upskilling programs, certifications, and hands-on experimentation are no longer optional, they are critical for ensuring employees at all levels understand AI’s capabilities and how to leverage them effectively.

"AI education isn’t optional anymore, it’s critical to ensuring your workforce is future-ready." – Beena Sukumaran, Ph.D., Dean, Miami University

Enterprise Insight: Develop tailored training programs that reflect the unique needs of your organization. For example, customer service teams might need training on AI-powered chat tools, while operations teams could benefit from hands-on sessions with predictive analytics platforms. Beyond technical skills, emphasize adaptability and problem-solving as core competencies.

Key Move for Leaders: Establish an internal AI academy or partner with external institutions to deliver role-specific training. Appoint “AI champions” within departments to support peers, share best practices, and provide ongoing guidance on integrating AI into workflows. Focus on experiential learning, true understanding of AI's potential comes from doing. Engage employees in real-world AI projects, commit resources to experimentation, and foster a culture of continuous improvement. Practical application builds confidence and drives deeper engagement, ensuring that teams not only learn but also internalize how to apply AI effectively in their roles.

3. Focus on the Workforce, Not Just the Technology

For years, enterprise investments in AI have been dominated by conversations about hardware, software, and cloud ecosystems. But success in AI is not simply about having the best technology, it’s about enabling the people who use it to drive results. Focusing exclusively on technology without equal emphasis on workforce empowerment leaves organizations vulnerable to failed adoption and wasted resources.

"It’s not just about building data centers; it’s about building a workforce that knows how to use AI to drive value." – Tonjia Coverdale, Ph.D., SVP, Associated Bank

Enterprise Insight: Shift the narrative from “technology-first” to “people-first” AI adoption. Ensure that employees understand how AI will enhance their roles rather than replace them. Regularly communicate the purpose and benefits of AI initiatives to foster trust and engagement.

Key Move for Leaders: Host monthly “AI innovation forums” where employees can share experiences, success stories, and challenges with AI integration. Create a feedback loop to adjust strategies based on employee insights and concerns.

4. Reimagine Core Industries with AI

AI isn’t just the domain of tech companies, it’s a game changer for traditional industries like manufacturing, healthcare, and financial services. Enterprises in these sectors can harness AI to optimize operations, personalize services, and reduce costs at scale. From automating repetitive tasks to driving deeper insights into customer needs, AI enables traditional industries to remain competitive in a rapidly changing marketplace.

"The opportunity isn’t just in new industries, it’s in revitalizing what we already do well." – Channie Mize

Enterprise Insight: Leaders should view AI as a revitalization tool that unlocks efficiencies and innovations in core industries. For example, manufacturers can leverage AI-driven predictive maintenance to reduce downtime, while healthcare providers can use AI for more accurate diagnostics and patient personalization.

Key Move for Leaders: Begin with pilot projects in areas with measurable outcomes, such as operational efficiency or customer retention. Use these pilots as a springboard for larger-scale AI initiatives.

5. Leverage AI for Business Resilience

In a world where disruption is the norm, resilience is becoming one of the most valuable traits for any enterprise. AI offers organizations powerful tools to predict and adapt to changes, whether those are shifts in customer demand, supply chain disruptions, or evolving market conditions. By embedding AI into decision-making processes, enterprises can not only respond to challenges but also anticipate them, gaining a critical edge over competitors.

"AI can democratize access to critical services, whether it’s healthcare in underserved communities or operational insights for small manufacturers." – Channie Mize

Enterprise Insight: Use AI to build resilience by enabling real-time data analysis and predictive capabilities. For example, supply chain managers can use AI to simulate scenarios and optimize inventory levels in response to fluctuating demand.

Key Move for Leaders: Develop AI-based dashboards for critical functions like supply chain, finance, and customer experience. These dashboards should provide actionable insights and forecasts that empower leaders to make informed decisions in real time.

6. Harness the Power of Agentic AI to Amplify Impact

As enterprises grapple with integrating AI, the rise of Agentic AI, AI systems designed to act autonomously within specific parameters, is creating transformative opportunities. Unlike traditional AI that requires constant human input, agentic AI allows organizations to streamline complex workflows, solve dynamic challenges, and act proactively based on real-time insights.

"Agentic AI allows us to create systems that aren’t just tools, they’re teammates. These systems drive efficiency and empower teams to focus on the innovation and creativity that only humans can deliver." – Channie Mize

Channie shared how Slalom, as a consulting firm, is already adapting to agentic AI’s impact on its business model. While AI introduces efficiencies that reduce the need for large teams, it also amplifies the strategic value consultants bring to the table.

"What we’re seeing with agentic AI is an opportunity to shift our focus from labor-intensive tasks to building intellectual property and delivering strategic innovation. AI doesn’t replace consultants, it makes us more agile and effective, enabling us to create better outcomes for our clients." – Channie Mize

For example, Slalom leverages agentic AI to automate data-heavy processes like fraud detection and logistics optimization. This allows consultants to dedicate more time to creative problem-solving, high-impact client interactions, and developing proprietary solutions that set the company apart.

Enterprise Insight: Integrate agentic AI into your organization to handle complex, repetitive processes autonomously. Identify areas where AI can take over high-volume, low-value tasks, freeing your teams to focus on strategic initiatives and innovation. Use agentic AI to enable faster iterations, better decision-making, and more meaningful collaboration across teams.

Key Move for Leaders: Start by implementing agentic AI in areas where routine, data-intensive tasks consume significant resources, such as customer support, logistics, or fraud detection. Platforms like FifthRow can streamline this process by automating complex workflows and enabling rapid deployment of agentic AI solutions tailored to your organization’s needs. Develop a framework for collaboration between AI systems and your teams, ensuring employees have the tools and training to work effectively with AI-generated insights. Simultaneously, evaluate how agentic AI can shift your organization’s focus toward creating long-term value through innovation and differentiation, leveraging solutions like FifthRow to scale and refine your approach.

7. Collaborate Across Ecosystems

AI innovation doesn’t happen in silos. The most successful organizations are those that actively collaborate with external partners, whether universities, startups, or other businesses. These partnerships bring in fresh perspectives, unlock access to cutting-edge research, and enable enterprises to stay ahead of the curve.

"AI adoption is a team sport. Collaboration between academia, industry, and government is critical to success." – Beena Sukumaran, Ph.D.

Enterprise Insight: Build an ecosystem of AI collaboration by forming alliances with universities for research and talent development, partnering with startups for niche innovations, and leveraging government initiatives for infrastructure support.

Key Move for Leaders: Create dedicated roles or teams to manage and grow these partnerships. Use them as a pipeline for new talent, ideas, and opportunities to stay competitive.

8. Democratize Access to AI and Address Digital Equity

While AI has the potential to transform industries, not all organizations, or individuals, have equal access to its benefits. For enterprises, ensuring that AI tools, training, and opportunities reach all levels of the workforce is not just a matter of fairness, it’s a strategic imperative.

"Equity isn’t a nice-to-have, it’s essential for long-term growth and innovation." – Channie Mize

Enterprise Insight: Conduct a comprehensive audit of your organization’s AI access and usage. Evaluate disparities in access to training, tools, or resources across departments and geographies, and develop a plan to address these gaps.

Key Move for Leaders: Implement programs that democratize AI, such as subsidized training, access to shared AI platforms, and mentorship programs for underrepresented groups in AI-driven roles.

9. Take the Long View: AI Is a Journey, Not a Quick Fix

It’s tempting to see AI as a solution to immediate problems, but true AI success requires a long-term perspective. Leaders need to recognize that AI adoption is a continuous process, one that evolves as technologies mature and organizational needs change.

"The winners in AI will be the ones who embed it into their culture, not just their technology stack." – Tonjia Coverdale, Ph.D.

Enterprise Insight: Develop a phased AI strategy that combines quick wins with exploratory initiatives. This ensures you deliver value in the short term while also investing in transformative projects that redefine your industry.

Key Move for Leaders: Establish a robust AI roadmap that aligns with your long-term strategic goals. Start with initiatives that deliver measurable outcomes within a year, such as automating customer support or streamlining supply chains. Simultaneously, set aside resources for exploratory projects that push the boundaries of innovation, like embedding AI into new product development or leveraging it for market disruption. Foster a culture that prioritizes learning and adaptability, encouraging teams to continuously refine and expand AI use cases over time.

Leading the AI-Driven Enterprise

AI is no longer a future promise, it’s a present reality delivering measurable value to enterprises worldwide. As Beena Sukumaran, Channie Mize, and Tonjia Coverdale emphasized during the panel, the organizations that succeed with AI will be those that think strategically, prioritize their people, and harness technology as a transformative enabler.

The challenge for enterprise leaders is clear: adopt AI with intention. Use it to solve meaningful problems, create value for your customers, and build a workforce that’s prepared for the future. With the right mindset and strategic approach, AI isn’t just a disruptor, it’s the foundation for a new era of enterprise growth and resilience.

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.