As such, levels of investment in AI technology are booming. For example, one company was recently able to raise $270 million on a valuation of $2.7 billion. AI companies raised almost $40 billion in investment during 2019, and this year will probably outpace the last. IDC predicts that spending on AI will approach $98 billion by 2023.
High levels of both investment and adoption point to a near future in which AI is ubiquitous. This is going to have marked effects on both the AI industry and on users of AI.
It used to be that if you were the first organization in your industry to adopt AI successfully, you’d gain a sizable competitive advantage over your peers. Research from Microsoft shows that companies who implement AI can outperform those that don’t by up to 11.5%.
This advantage is going to disappear, because soon enough every company in every industry is going to adopt an AI suite that includes mission-critical technologies (machine learning, deep learning, intelligent automation, natural language processing) and enjoy that 11.5% bump. Instead of merely adopting AI, companies will need to adopt it creatively, adopt best-in-class products, or use AI as a competitive differentiator instead of simply to improve efficiency.
As AI achieves its early majority, companies will need to find new ways of implementing AI to continue gaining advantages over their competitors. This can be a tall order, especially when you consider that over 90% of organizations have reported an AI project failure. Reasons for failure include technology that didn’t fit the bill, lack of staff experience, mismatched business cases, and simple lack of follow-through.
This report—and many other stories that talk about the failure rate of AI products—would seem to indicate that AI is hard to get right. This seems at odds with the idea that AI will feature prominently in most enterprises within the next three years—and it might bode ill for companies looking for novel AI use-cases.
On the other hand, the rapid maturity of AI products indicates that they’re becoming easier and easier to implement. By the time AI hits its projected saturation point in 2023, installing and using an AI solution will probably be easier in ways that we can only guess at—they may be as easy as implementing a SaaS solution is today. With that in mind, only those trying to find new AI use cases will likely experience elevated risks.
So, what will creative approaches to AI look like in the future?
To summarize, companies that have already adopted AI—or who are planning on near-term adoption—can’t rest on their laurels. Currently, levels of investment in AI indicate that most enterprises will still be on a level playing field again. To maintain market dominance, incumbent AI adopters should already be thinking of how they’ll make their next moves with this technology.
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