First Steps for Planning AI Strategy

Executives across industries are under pressure to determine how AI fits into their growth strategies, competitive positioning, and long-term value creation. Yet, for many mid-market organizations, the challenge isn’t why AI matters, it’s how to start planning effectively.

At Thrive, we see too many businesses rushing into AI without a clear strategy, only to waste resources or introduce risk. Instead, the first steps toward AI adoption should be deliberate and business-driven; research has shown that 95% of AI projects fail to hit any cost savings or revenue generation.

1. Start with Strategic Objectives

AI is a means to an end, not the end itself. Before considering tools or platforms, identify the outcomes that matter most to your business, such as:

• Improving profitability by reducing operational inefficiencies.
• Enhancing customer retention through personalized experiences.
• Strengthening resilience by predicting and mitigating risks.

Framing AI use in terms of measurable business objectives can make sure that every initiative contributes to growth or stability, not just experimentation.

2. Evaluate Organizational Readiness

AI success isn’t just about data or algorithms, it’s about whether your business is prepared to integrate new capabilities. Key business-focused questions to ask:

• Do you have leadership buy-in for AI initiatives?
• Who will lead this AI initiative?
• Are your teams aligned on where AI can deliver value?
• Do you have a plan for risk management, governance, and compliance?

An AI readiness assessment prevents wasted effort and helps prioritize realistic organizational initiatives.

3. Identify High-Value, Low-Risk Use Cases

The best AI strategies begin with targeted wins. Instead of trying to transform your organization overnight, focus on initiatives that are impactful yet manageable. For example:

• Streamlining back-office operations to reduce costs
• Enhancing customer support with AI-driven insights
• Leveraging predictive analytics to improve decision-making

These focused, smaller projects prove value, generate momentum, and help build internal trust and executive buy-in for AI.

4. Establish Guardrails Early

AI introduces new risks for organizations, such as bias, misinformation, compliance gaps, and security vulnerabilities. Leaders should define governance policies before scaling adoption. This means setting clear standards for:

• Responsible data usage
• Alignment with regulatory requirements
• Transparency and accountability in automated decision-making

By putting governance first, businesses avoid reputational risk and maintain stakeholder confidence.

5. Invest in People and Change Management

AI won’t succeed in isolation. Leaders of organizations must equip their teams with the knowledge, training, and confidence to use AI effectively. More importantly, they need to foster a culture where AI is seen as a tool to enhance decision-making and efficiency, not replace jobs. Successful AI strategies balance technological investment with organizational alignment.

An AI strategy is not a technology roadmap, but a business roadmap powered by technology. By starting with strategic objectives, aligning your organization, selecting the right use cases, embedding governance, and supporting your people, you can create a foundation for sustainable, value-driven AI adoption.

Thrive helps mid-market businesses take their first steps with AI the right way: focused on outcomes, compliance, and long-term growth. Contact Thrive today to learn more about how AI fits into your business strategy, from planning to execution.