AI’s transformative and vast potential is reshaping the business landscape, compelling executive leaders to consider whether they are truly leveraging AI for maximum benefit. Adopting an AI first strategy means making a deliberate commitment to explore and evaluate AI’s capabilities in critical areas of investment and application. Gartner predicts that by 2028, enterprises that adopt and sustain an AI-first strategy across their organization will achieve 25 percent better business outcomes than competitors that do not.
For enterprises to embody AI-first thinking in their strategy and related investment, portfolio, and execution management practices, it is important to understand the true meaning of the AI-first approach.
What Is AI-First?
AI-first is a strategic approach that guides the use of AI technology in an enterprise, or for a unit within, to maximize the benefits of AI. Rather than treating AI just as a tool, AI first means always considering its full potential and possibilities against other choices and using it where it makes the most sense.
AI-first accelerates AI adoption, improves AI literacy, fosters continuous learning and helps uncover new possibilities that might otherwise be missed. Most importantly, an AI first strategy is not a rigid mandate to always use AI, it’s a commitment to exploring its merit in every situation.
Organizations can implement AI-first in various ways, from an enterprisewide transformation to focusing on specific areas like product development, IT systems, or HR practices. The greatest benefits come when organizations break down silos and maximize cross-functional opportunities.
Adopting an AI-first strategy requires commitment from senior leadership, clear communication and robust support system for change management. It also demands new ways of measuring success—tracking shifts in behaviors, mindsets and the quality of learning—while maintaining rigorous standards around ethics, bias management and security.
When to Embrace AI-first Approach?
Determining the right time to adopt an AI-first strategy is critical for organizations seeking to maximize the value of their AI investments. While organizations are investing in AI, they consistently struggle to maximize its value.
An AI-first approach becomes especially urgent when there is a widening gap between the perceived promise of AI and the value delivered by current use cases, or when existing systems and mindsets are barriers to meaningful change.
Key Indicators for Adoption
Consider moving towards an AI-first Strategy when:
- The gap between AI’s perceived potential and the value of currently proposed use cases is widening.
- The potential for large-scale disruption or transformation due to AI is high.
- Executive leadership is ready to encourage and enable transformational changes, but the remainder of the organization is ill-prepared and unable or unwilling to conceive broad change.
It’s important to remember that “AI-first” does not mean “AI always.” Forcing adoption where it isn’t merited can lead to wasted resources, failed projects and diminished organizational support. Leadership must clearly define what being “AI-first” means within their context—including its scope and limitations—to set realistic expectations.
A careful strategic assessment should guide when and how to commit to an AI-first path. Moving too soon can result in wasted effort if the organization isn’t ready. Likewise, waiting too long risks falling behind competitors or missing out on market opportunities. While there are similarities with cloud-first strategies, such as elevating technology as a key decision factor, adopting an AI-first mindset goes further by challenging entrenched beliefs and fostering innovation across all business areas, not just infrastructure.
By Rajesh Kandaswamy, Distinguished VP Analyst at Gartner
