Many companies may consider adopting artificial intelligence (AI) to be a no-brainer. Given the ever-increasing availability of AI tools and use cases that demonstrate its benefits, business leaders across industries consider its implementation necessary to maintain a competitive edge.

The problem? AI may be the future, but many companies are only planning for the short term and don’t have fully mature systems in place to handle its demands. Two-thirds (67%) of companies only have a vision for AI that extends a year or less into the future, and less than half (45%) are confident their use of cloud services can handle AI for the next year.

Whether an organization is just beginning to explore how to best implement AI or is currently adopting AI solutions, having a well-defined AI strategy is essential for maximizing return on investment. Given the high cost of implementing AI solutions and the fact that organizations can't adjust staffing levels or cut costs until the value of an AI tool is proven, the short-term financial outlook for AI projects won’t always look attractive. A long-term mindset is critical to recognizing the financial benefits of AI solutions.

Organizations can take various approaches to refining their AI strategy and gaining leadership support to drive success.

The Core Components of a Strong AI Strategy

What does it mean to develop an AI strategy? To define a clear AI strategy, AI initiatives must be aligned with long-term business objectives while securing leadership buy-in across the organization.

Organizations that excel in deploying AI typically:

• Determine specific challenges that AI can address
• Establish clear, actionable goals for its implementation
• Develop a structured AI plan that covers at least the next 12 months
• Appoint a dedicated leader or team to drive AI initiatives
• Focus on long-term ROI, recognizing that upfront costs can be significant
• Define key performance indicators (KPIs) to measure success

How to Build an AI Strategy and Secure Leadership Buy-In

Companies are racing to integrate AI, but jumping in without a strategic foundation can lead to failure, as 80% of AI projects ultimately fail.

One common pitfall is that teams often lack a clear understanding of the problems AI is meant to solve. Instead of focusing on how AI can enhance operations, user experience, or other technologies, organizations may become overly fixated on the technology itself.

Without a defined goal and strong leadership involvement, AI initiatives risk falling short before they even get started. AI transformation is an ongoing journey, not a one-time project. To stay ahead, organizations need to continuously refine their AI strategy.

The key steps to achieve this include:

      1. Aligning AI Initiatives with Business Goals

Start by pinpointing a business problem AI can solve. Are you looking to enhance customer experiences with personalized recommendations? Or perhaps you want to strengthen cybersecurity by detecting vulnerabilities faster? Defining your end goal ensures AI investments drive meaningful outcomes.

Once an objective is identified, set clear, measurable goals for AI implementation. Pluralsight research has shown that 54% of organizations lack well-defined goals for AI adoption. While broad ideas are a great starting point, turning them into concrete action plans is critical for long-term success.

      2. Gain Leadership Support for AI Initiatives

AI funding is a priority for many businesses, as 66% report aggressively investing in AI initiatives. This level of investment is only possible because leaders recognize AI’s value.

To secure leadership buy-in, appoint budget decision-makers, and align AI proposals with their priorities and KPIs. It’s also important to appoint an AI champion to lead the initiative, oversee implementation, and identify external factors like compliance requirements or risk management. These champions must also be prepared to overcome objectives from leaders who are leery of change. Some colleagues, regardless of the potential benefits to others, may ignore or even disrupt AI initiatives to defend the status quo. Oftentimes this resistance is based on fear of the unknown or shifting power structures.

     3. Develop a Long-Term Plan

Only a third of organizations have AI strategies that extend beyond a single year, leaving most companies operating with short-term plans.

For AI to drive sustainable impact, organizations need a long-term vision. Outline a structured plan covering at least one year into the future. While the strategy evolves, thinking beyond short-term experimentation demonstrates a serious commitment to AI as part of an overall business strategy.

     4. Establish KPIs to Measure ROI

Tracking AI’s impact goes beyond subjective benefits like making work easier for employees. Setting clear KPIs helps determine whether AI is truly delivering value. Key metrics to assess AI success include productivity gains, revenue growth, and AI pilot projects transitioning into full production.

Additional metrics will depend on AI use cases. For example, if AI is used for cybersecurity, success indicators can include detection rates, response times, and cost savings. For data analysis, KPIs should include decision-making speed, accuracy, and time efficiency.

Take Your AI Strategy to the Next Level

AI adoption is not just about where your organization stands today—it’s about understanding your current position and identifying opportunities for growth. By refining your strategy and securing leadership buy-in, you can advance your organization’s AI maturity and drive greater success.