Seven Things Artificial Intelligence Won’t Do

Despite the amazing potential of Artificial Intelligence (AI), there are some things it just won’t do. If not properly addressed, these considerations can become immovable barriers to AI adoption. As you may already suspect, they have very little to do with the technology itself or the availability of scarce experts which is – in and of itself – a formidable obstacle.

So what won’t AI do?

Justify Itself. Yes, AI is being wielded in increasingly public, visible ways. Yes, value propositions and practical proofs abound. This doesn’t mean your organization is ready to jump headlong into AI, no matter the prospective value.  Despite AI’s potentially titanic effect on business-as-usual and the fact Artificial Intelligence has been decades in the making AI is, for all practical purposes, an emerging technology.

If your company has a means to support innovation (be it a lab or R&D programs for speculative business development), you have a head start. If not, you may need to tame your enthusiasm for green field projects and wholesale redesigns. Instead, target well understood and bounded problems (hint: existing, tactical, operational) with clear, justifiable ROI as an initial proving ground.

Explain Itself. How Artificial Intelligence reaches a conclusion is often ambiguous, at best. In most cases, solutions – particularly those based on Deep Learning and other Machine Learning (ML) techniques – remain black boxes. Numerous techniques are being explored to allow AI’s internal logic to be modeled and visualized. Even, in future, for AI solutions themselves to explain how they got from A to Z. We aren’t there yet. Unambiguously assessing and addressing your organization’s willingness and ability to act in the face of ambiguity is critical.

Perform Flawlessly. Make no mistake, AI is human too. The best trained and tuned AI solution will make mistakes. Be they big or small, acknowledging the limitations of AI allows the appropriate interaction model and guardrails to be deployed. Thereby ensuring material mistakes don’t result in mission critical failures or negatively impact key customer relationships. In some cases, this means AI needs to serve as a collaborator or expert advisor, assisting the decision maker. In others, AI may function autonomously – making independent decisions and directly interacting with other systems, end users or customers.

Solve Your Data Dilemma.