
Trustrorthy AI
Knowledge Base
Executive Vision
We’ve tried in vain over the years to accommodate shortcuts demanded by various organizations with whom we’ve worked. Alas, we’ve reached the same conclusion each time: Technology adoption fails when not driven by executive vision. Adopting AI is simply too challenging for most organizations to do when absent of long-term vision supported from top-down. You simply must define the organizational direction of travel for AI at the CXO level.
This is the stuff of many, many business leadership books written over the years, so we don’t want to be too prescriptive here. Executive vision can take many forms, but the bottom line is that your executive vision for AI (or any technology) must frame everything that follows so that it is crystal clear why the organization is embracing this technology and what the organization collectively aspires to achieve from its adoption.
We’ve helped many organizations craft their vision for AI. The anonymized aspirations below provide a great example of a top-level executive vision at a real-world enterprise firm.
Figure 5 : A top-level executive vision for AI framing the aspirations for an organization embracing AI. This example includes building a digitally literate culture, creating a scalable and composable cloud ecosystem, extracting value from data safely, adopting a future-ready mindset and increasing AI knowledge and expertise.
Notice that our vision is aspirational, succinctly describing not just what we hope to achieve with artificial intelligence, but what we hope to be as an organization that has embraced artificial intelligence. Further, only two of our five aspirations explicitly mention AI at all. This is important: We often hear folks talk of AI as if it were a product, but it’s not a product at all. AI is quickly being woven through nearly every aspect of our work lives (and our lives in general), and it equally depends on the proper functioning of other domains including data, applications, technical governance, business process, digital culture, and the mission of the organization itself (“improving client engagement”, in the case of the example above).
Finally, a well-crafted executive vision ought to go beyond headline aspirations to describe what we call “targeted outcomes”, which is to say, to define the outcomes the organization hopes to achieve in actualizing its aspirations. Think of targeted outcomes as adding specificity to your aspirations, not necessarily hard, quantifiable specificity, but a clear articulation of what it means to (for example) “Extract increasing value from our data using responsible, safely leveraged artificial intelligence”:
• The data platform offers a mastered single source of truth for the most mission critical data domains;
• Data is addressable by AI and aggregated from different sources as part of our data platform;
• AI is deployed consistently and with governance guardrails in place;
• "Low-hanging fruit" (incremental) AI capabilities quickly deliver lower-risk capabilities to our colleagues;
• We pursue a risk-sensitive portfolio of "differential AI" customized for the firm.
Whatever your executive vision, it is important to lead with it, to prioritize the AI investments that best align to it, and to evangelize it such that colleagues both in IT and the wider business understand the all-important “why”.