Stop Talking to Vendors

Your inbox is likely overflowing with invitations from vendors who promise revolutionary AI platforms that will transform your business.

Why it matters: For executives navigating the journey into Enterprise AI, the biggest mistake is starting by engaging with vendors.

• Talking to solution providers before identifying your problems is like asking a yacht broker to secure a vessel without knowing whether you need to cross a river or an ocean.

• This approach can lead to an expensive and ill-suited solution for a problem that you never clearly defined.

Yes, but: The correct first step in a successful AI transformation is not to look outward but to start from within.

• It begins with education, fosters a common language, and culminates in a strategy that is developed through internal alignment, rather than external capabilities.

Between the lines: Before you can build an AI strategy, your organization must be able to have a coherent discussion about AI.

• This is impossible when the CEO's understanding of a Large Language Model (LLM) comes from a news headline, the CFO's from a vendor pitch, and the CRO's from a sci-fi movie.

State of play: The foundational first step is to bring in qualified, vendor-agnostic trainers to conduct AI literacy workshops for your entire leadership team, from the C-suite to department heads and key project managers.

• The goal here is not to transform executives into data scientists, but to establish a shared foundational vocabulary and conceptual understanding among them.

Catch up quick: The immediate outcome of this educational phase is the most valuable asset at the early stage of your AI journey: a common language.

• When everyone understands the basic concepts, the hype fades away, and productive, cross-functional conversations can finally begin.

Zoom in: This internal planning phase should focus on identifying and prioritizing use cases.

• A simple framework can be very effective: map potential projects on a 2x2 matrix of business value versus technical feasibility.

• Your newly educated team will be much better equipped to estimate both.

What's next: For instance, the finance team might identify a high-value, high-feasibility project in automating invoice analysis.

• In contrast, the marketing team might propose a project using generative AI to create campaign drafts.

• Crucially, because both teams now speak the same language, they can collaborate with IT to realistically assess resource needs and potential pitfalls.

The outcome: A prioritized roadmap is a strategic document that identifies 2 to 3 initial projects closely aligned with business needs and with a high likelihood of success.

• Once you have this clear and internally approved plan, you should then reach out to the specific vendors that can provide the necessary resources.

Go deeper: Contact Todd Moses & Co for a free book on this topic, a review of your AI strategy, or to arrange AI Literacy training.