“Starting in 2020 several well-funded industrially-focused AI/ML vendors will fail as the focus shifts from generic approaches to outcome-based approaches.” – Momenta Partners 2020 Predictions
The rush to deploy artificial intelligence (AI) or even machine learning (ML) at industrial enterprises around the globe as well as the concurrent rush by all manner of investor to invest in industrially-focused AI/ML companies or initiatives is too often “a solution in search of a problem.” Don’t get me wrong. There will be a role for these technologies for an industrial world in need of greater predictability and control of their operations. But the better, near term return on investment is simply capturing, aggregating, and sharing industrial data more widely.
The generic AI/ML vendors too often start with an “if you build it they will come” strategy. This assumption is reinforced by just enough users who are intrigued by the possibilities of the technology to invest in the solution and start pilot projects. They are willing to put aside the vendor’s lack of grounding in the industrial world on the promise of a big win. Yet, even in cases where millions of dollars have been invested in these AI/ML projects, there are more failures than successes. This is just one of several signs that the hype is reaching its natural peak and the market will experience some form of rationalization starting in 2020.
Industrial companies looking to invest in AI/ML would be advised to carefully evaluate whose products or services they choose to buy. And, more fundamentally, whether AI/ML might not be the best fit for the problems they are attempting to solve. The vendors often pitch it as a panacea that will fix all manner of problem but even the most carefully conceived AI/ML projects will fail for lack of the right data or, where the data is theoretically available, where the data quality is poor. Diagnosing operational performance or machine health is not the same as analyzing consumer preferences where getting it mostly right, half of the time is considered a success!
Most industrial organizations would see significant benefits from simply having greater visibility to the data they already have; much of which is locked up in disparate systems across their extended operations.In this context visibility = access + meaning + visualization. Cloud technology provides data access, fit for purpose analytical tools provide meaning, and visualization tools include simple 2D graphics to 3D virtual models with augmented reality (AR). These tools/services are all readily available, increasingly cost effective, and, in many cases, tailored by industry-focused vendors to address known challenges or opportunities.
Momenta Partner’s research has found that most companies aren’t there today. The first step, then, is to invest in organization-wide visibility. The next step is to look at ways to establish data sharing arrangements with partners and customers (see The Industrial Ecosystem Imperative). These two steps alone have proven to deliver measurable business value. And when the time comes in the future to invest in AI/ML the foundation will have been laid for success. The old adage “walk before you run” most certainly applies in this context.
“Continuous improvement is better than delayed perfection.” – Mark Twain
If you would like to learn more about Momenta Partners view of industrially-focused AI/ML and our perspective on the vendor landscape, reach out to me at firstname.lastname@example.org. You can also explore more from our Insights page.
Momenta Partners encompasses leading Strategic Advisory, Talent, and Venture practices. We’re the guiding hand behind leading industrials’ IoT strategies, over 200 IoT leadership placements, and 25+ young IoT disruptors. Schedule a free consultation to learn more about our Connected Industry practice.