Start With Easy

tl;dr - Everyone is interested in innovation, but they’re not interested in putting in the work.

Part 4 of #x series discussing the use of Intelligent Data platforms and Artificial Intelligence systems.

Knowledge gaps, skepticism, and fear mean that your best starting point for AI is a simple and incremental project.

While the promise of AI is to disrupt organizations and industries alike, these kinds of innovative projects can frankly be exhausting. Particularly when your organization lacks the knowledge and/or appetite for AI-driven change, the best course of action to get people interested in building a real AI practice is to start with a simple, straightforward, easy, and even dull project. Though your own data & AI teams may moan at the monotony of these projects, they are critical to building trust and highlighting the value in investing in AI at an organizational level. Participants who tried to run before they could walk acknowledged that they may have set their organization’s AI efforts back months or years through overly ambitious initial projects that failed to live up to expectations or failed completely because the org wasn’t ready.

The Implications?

People I have spoken with recently acknowledged that their AI journeys started with off-the-shelf (OTS) AI add-ons from established service providers for things like cybersecurity and IT monitoring. OTS was described by one person as a “gateway drug” to AI… but a necessary one that gave senior leadership the proof to invest further. These sorts of simple, straightforward, quick-win projects are a key step in the journey of evolving an organization’s comfort and mindset around AI.

How has your experience been?