How will enterprises manage artificial intelligence deployments when most managers and executives don't understand the underlying models, data science, or technology?
That question is almost haunting. Artificial intelligence (AI for short) is lumped together with big data, machine learning, and neural networks to create what equates to a technology buzzword orgy. And if you want another theme toss in cloud computing, which is the enabler for AI.
Sure, we know AI is a bit hyped. And, yes, we may not quite know the underlying details of AI and what it means for our businesses. But, damn, we just can't resist the dream of black box thinking and something that can take our data lakes and give us insight. The appeal of AI to the enterprise is akin to the average bear who wants a pill to replicate exercise (without the work of course) and keep us young forever.
Simply put, we're AI happy. We've already previewed the AI washing, but all the surveys in the last month point to CXOs that are gaga for artificial intelligence. Consider:
Accenture timed its AI survey for the Davos powwow last week. The upshot: 72 percent of the 1,200 senior executives surveyed by Accenture said intelligent technology will be critical to their organization's market differentiation.
Sixty-one percent of respondents to that Accenture survey said that the share of roles requiring AI will rise in the next three years.
Infosys research, based on a survey of more than 1,000 business and IT leaders, found that AI is moving past experimentations to deployment. Infosys found that 73 percent of respondents agreed that their AI deployments have already transformed the way they do business.
According to Infosys, 86 percent of organizations surveyed said have middle to late-state AI deployments underway.
TD Bank bought an AI company called Layer 6 to bolster new customer experiences.
Narrative Science found in its own research that AI adoption grew more than 60 percent in the last year.
Constellation Research's Ray Wang noted in a recent report:
Now, searching for a competitive advantage and fearful of disruption, boardrooms and CXOs have rushed to AI as the next big thing. The investment in pilots for AI's subsets of machine learning, deep learning, natural language processing and cognitive computing have moved from science projects to new digital business models powered by smart service.
At a Temple University analytics conference last year, the management question was raised. The theme from C-level folks was that you have to strive to avoid black box decision-making because the analytics can be skewed by your underlying data quality. Memo to enterprises: Chances are your data quality is far from solid. Even if you have solid data quality, it's unclear that most of the line of business executives will rely on AI and models they can't possibly understand. AI is in the middle of a deployment land grab today. Tomorrow the business management headaches will arrive.
The Monday Morning Opener is our opening salvo for the week in tech. Since we run a global site, this editorial publishes on Monday at 8:00am AEST in Sydney, Australia, which is 6:00pm Eastern Time on Sunday in the US. It is written by a member of ZDNet's global editorial board, which is comprised of our lead editors across Asia, Australia, Europe, and the US.