Artificial Intelligence (AI) can deliver transformative benefits, but it also sparks unease among executives and employees alike. Aaron Bland Moore, a fractional Chief AI Officer (CAIO) and CTO, has seen how these apprehensions can stall innovation. With 34 years of cross-industry experience, he believes the best way to address AI fears is through a well-defined strategy—one that clarifies both risks and opportunities.
Facing the Fear of Disruption
Many organizations worry they’ll be caught off guard by AI-driven competitors or that they’ll invest heavily in AI without real returns. In some cases, leaders simply don’t know where to begin. Moore notes that while these fears are valid, the bigger risk is doing nothing at all. “Either you move forward,” he often says, “or risk getting left behind when others do.”
By partnering with PE-backed firms, Moore has found that honest assessments of potential blind spots can turn anxiety into action. This includes evaluating how AI might upend existing business models—and how organizations can pivot to become the disruptors, rather than the disrupted.
Aligning Teams Through Strategy
To overcome uncertainty, Moore advocates for an AI strategy that fosters alignment. First, he evaluates a company’s current capabilities—data readiness, infrastructure, and team skill sets. With this baseline in mind, leadership can make informed decisions about which AI initiatives to pursue and which to set aside.
Moore’s method also emphasizes transparent communication among stakeholders. When teams see how AI fits into broader business goals—such as boosting revenue or enhancing customer satisfaction—they become less resistant to change. This alignment not only reduces fear but positions AI as a meaningful growth driver.
Finding Portfolio-Wide Synergies
For a Private Equity principal overseeing multiple companies, one major advantage of an AI strategy is the possibility of replicating successes across the portfolio. Aaron often identifies common challenges—like inefficient customer-service workflows or outdated data pipelines—that can be tackled with a single AI platform or shared set of best practices. By rolling out proven solutions to multiple businesses, PE leaders not only save on costs but also accelerate time to value. This collective approach to AI amplifies returns and strengthens the competitive edge of every portfolio company involved.
Navigating the Buy-vs.-Build Decision
One of the most critical elements in overcoming AI-related apprehensions is choosing the right solution path—buying an off-the-shelf platform or building an in-house system. Moore notes that buying can accelerate deployment and minimize some technical risks, since most commercial solutions come with user support and proven use cases. On the other hand, building in-house often offers greater customization and long-term flexibility but may demand significant resources, specialized skills, and more time to achieve success.
For organizations already wary of AI’s complexity, making this choice can be daunting. Moore helps teams weigh the trade-offs by examining each option’s cost, timeline, talent requirements, and strategic fit. Ultimately, selecting the right mix—buying for quick wins and building where custom approaches are essential—can reduce anxiety and ensure a smoother AI journey.
Transforming Risk into Opportunity
A robust AI strategy does more than quell fears; it can unlock new markets, boost operational efficiency, and fortify a company’s competitive position. Whether that means adopting a powerful ready-made AI platform or crafting a unique in-house solution, Moore pairs practical quick wins with a long-term vision that sets firms up for success.
In a fast-evolving tech landscape, organizations that approach AI with thoughtful planning will likely outpace those that hesitate. For Moore, the question is clear: “Do you want to be disrupted, or do you want to be the disruptor?”
To connect with Aaron Bland Moore or learn more about his approach, visit:
www.aaronblandmoore.com
