By Baker Tilly’s Chris Wagner and Dave DuVarney
Artificial intelligence has quickly moved from an experimental technology to a boardroom priority. Leadership teams across industries are being asked the same question: What is our AI strategy?
Despite the growing pressure, many organizations struggle to answer that question. AI can feel powerful but ambiguous, and without a clear starting point, initiatives often stall or fail to deliver results. In fact, a significant percentage of AI initiatives fail to produce meaningful outcomes in their first year.
The organizations that succeed with AI tend to take a structured but practical approach — balancing leadership direction, experimentation, governance and a focus on real business problems.
Start with executive alignment
Successful AI adoption begins with leadership. Without executive support, AI efforts often remain scattered experiments rather than strategic initiatives.
Leaders don’t need to start with a massive strategy document. What matters most is establishing clear intent: AI is important to the organization, and exploring its potential is a priority.
When executives actively encourage teams to explore AI — asking how it might improve workflows or create new capabilities — it signals that innovation is expected and supported. This tone from the top creates the momentum organizations need to begin experimenting and learning.
Build a cross-functional AI team
Although AI relies on technology, it cannot succeed as an IT-only initiative.
Organizations benefit from forming a cross-functional team responsible for guiding AI adoption. This group typically includes representatives from technology, operations, finance, marketing and other key business functions.
Their role is to help the organization move forward intentionally by:
- Identifying and prioritizing potential AI use cases
- Establishing governance and risk policies
- Selecting enterprise AI tools
- Encouraging adoption across departments
- Developing business cases for investment
This team acts as the internal steering function that balances experimentation with strategic alignment.
Encourage Grassroots Innovation
One of the most transformative aspects of modern AI, especially generative AI, is its accessibility. Employees across the organization can experiment with these tools to solve everyday problems.
Organizations can benefit from encouraging this experimentation and capturing the best ideas. A simple innovation funnel can help:
- Employees experiment with AI tools.
- Promising ideas are shared with the organization.
- The most impactful use cases are evaluated and expanded.
Many AI platforms also provide usage data that can highlight successful workflows. If a particular tool or process becomes widely used internally, it may signal an opportunity to formalize and scale that solution across the organization.
Focus on problems, not technology
A common mistake organizations make is starting with the question, "Where can we use AI?”
A better approach is to start with the problem. Ask, “What business challenge are we trying to solve?”
Sometimes AI will be the best solution. Other times, simpler tools, such as spreadsheets, automation platforms, or traditional analytics, may be more effective.
Treating AI as one tool among many ensures that organizations apply it where it truly creates value rather than forcing it into every problem.
Capture everyday productivity gains
Not every AI benefit comes from large transformation projects. Some of the most immediate value comes from small improvements in daily work.
Employees are already using AI tools to help with tasks like:
- Drafting emails and reports
- Summarizing information
- Brainstorming ideas
- Structuring plans and strategies
- Working through complex problems
These small efficiencies may be difficult to measure individually, but when multiplied across an entire workforce, they can significantly improve productivity and job satisfaction.
Over time, this also helps employees become more comfortable and creative with AI tools, which can lead to larger innovation opportunities.
Strengthen governance and security
Security concerns are one of the biggest barriers organizations face when adopting AI. Leaders worry about sensitive data exposure, regulatory risks and the rapid growth of AI tools.
Addressing these concerns requires a thoughtful approach.
Provide enterprise-grade AI tools
Organizations should offer secure AI platforms within their own environments. If employees lack access to approved tools, they will likely use public alternatives, which increases risk.
Providing enterprise tools gives employees a safe place to experiment.
Extend existing data policies
Most organizations already have data governance policies. AI policies should simply extend those rules.
For example, sensitive company data should only be used within approved platforms rather than public AI tools.
Clear guidelines help employees understand how to use AI responsibly while still enabling innovation.
Review security practices
AI systems often interact with large volumes of organizational data, which can expose weaknesses in existing access controls.
Organizations should review how administrative privileges and sensitive data access are managed. Strengthening these controls ensures AI tools do not unintentionally expand access to information.
Learn from external expertise
AI technology is evolving quickly, and many organizations lack deep expertise internally.
Leaders can accelerate progress by learning from external sources such as:
- Industry communities and professional groups
- Peer organizations experimenting with AI
- Advisors and technology partners
- Educational resources and training programs
These networks help organizations stay informed, avoid common mistakes and move forward with greater confidence.
Moving forward with AI
Organizations don’t need a perfect strategy before they begin exploring AI. What matters most is creating the right environment for progress.
That environment includes:
- Clear leadership support
- Cross-functional collaboration
- Safe experimentation
- Strong governance and security
- A focus on real business problems
By combining these elements, organizations can move beyond the hype surrounding AI and begin realizing real value — one practical use case at a time.
How we can help
Baker Tilly helps organizations safely and effectively harness AI. Our AI consulting services support you from strategy development through implementation, including model design, data and AI governance, workflow automation and organizational readiness programs. Ready to accelerate your AI journey? Connect with a Baker Tilly specialist to get started.
