In the previous article, we explored what it means to diagnose and futurecast roles. This article takes the next step: using the resulting insights to build leadership support and begin moving the organization forward. Lessons from earlier periods of technological disruption can help us understand why leaders may hesitate—and how to make the case for action.
In the 1970s and 1980s, technological disruption was characterized by distinct solutions designed for specific purposes. Consider ATMs, early cellular phones, and personal computers. Each represented a meaningful technological advancement, but their applications were relatively independent and defined.
In some ways, this resembles where we are with AI today. Thousands of solutions are available, many designed for highly specific use cases. The sheer number of tools and possibilities can make it difficult for leaders to determine what is relevant, where to begin, and which opportunities warrant investment. When the options feel endless and the path forward remains unclear, waiting can seem like the safest choice.
Active experimentation offers a way to overcome that inertia. Exposing employees to practical AI applications and involving them in generating ideas helps organizations identify opportunities relevant to their work. This is why we recommend the diagnosis and futurecasting process introduced in Part 2.
With futurecasting results for a small number of high-impact roles, you are better positioned to gain buy-in from your CEO or board. Sharing potential changes to work activities, employee-generated ideas, and identified risks gives you a stronger basis for the conversation.
Diagnosis and futurecasting are designed with the end in mind: using data to explain AI’s potential impacts and opportunities. Rather than asking leaders to support AI in the abstract, you can show how specific applications could change work within your organization.
Establishing a baseline—how work is performed today—and estimating potential changes brings financial discipline to the discussion. It allows leaders to assess the opportunity against current performance and understand the assumptions behind the estimates. Developing use cases with the employees affected by those changes also reflects sound change management, which we explore further in Part 5.
Understanding your CEO’s or board’s priorities is essential to making the case. Whether leadership is focused on cost reduction, revenue growth, innovation, or customer satisfaction, explain how the proposed AI application could advance those objectives.
Tailor your argument to the audience’s financial, operational, or strategic concerns. Highlight the potential for measurable returns, improved efficiency and productivity, or a meaningful competitive advantage. The strongest case starts with an organizational need and shows how AI could help address it.
As opportunities become clearer, organizations must also consider what changing work will mean for their employees. In Part 4, we explore why a skills-based view of work is essential to implementing AI.
Thanks for reading. Let’s talk AI implementation. Send me a note at wade@batonglobal.com.
About Wade Britt
Wade Hampton Britt, IV is a partner and the Managing Director at Bâton Global. He has lived and worked in a dozen countries in the global express and edtech sectors before joining Bâton Global in 2016. Wade is passionate about helping clients and their communities navigate the AI disruption better than previous technological changes.
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