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Is AI Adoption Reaching a Plateau?

Artificial intelligence is one of the hottest and most innovative forms of tech out there right now, and many businesses are adopting it across the world. A new report from McKinsey confirms a lot of one might expect, revealing a huge increase in the adoption rate for AI among business enterprises with all things having been considered and taken into account. In spite of the fact that this is the case, AI adoption also seems to be hitting a bit of a plateau, with many noting a deceleration or perhaps even stagnation in its growth rate.

63% of businesses are planning to pour more investments into AI over the next three years because of the fact that this is the sort of thing that could potentially end up streamlining many of their processes. Adoption rates have also more than doubled in the past five years, going from 20% in 2017 to 50% in 2022. With all of that having been said and now out of the way, it is important to note that adoption rates have stopped growing at the same pace as of late.

Adoption rates are currently struggling to pass the 60% mark, and that suggests that total AI adoption may take a lot longer than might have been the case otherwise. However, companies that have already adopted AI are increasing the number of things that they might use it for. Companies that have managed to extract any sort of value from AI see an immediate eightfold increase in the likelihood of them spending over 20% of their tech budgets on it in the coming years.



One thing that might stall AI adoption growth is the lack of immediately apparent value. AI all on its own is not going to automatically fix problems that organizations might be facing. Rather, these companies would need to come up with adequate strategies that can help them implement it more effectively. The right strategy can do wonders for the efficacy of AI, and organizations that are using it need to continuously collect insights that can make it more valuable and useful in the long run.

Another thing that this report revealed was the lack of understanding of the risks associated with AI. Bias and cybersecurity are both important factors that should be considered while using AI, and organizations that are currently adoption it seem unwilling to accept them right now. It might just be a matter of gaining more experience, though. Organizations that have managed to become high performers seem to be more aware of its risks, and that might make them more capable of mitigating said risks down the line.

A major indication that organizations are considering heavier investments into the AI space is the increase in job postings for related roles. Software and data engineers are now being asked about their experience with AI, and it might become an increasingly important criteria for obtaining high paying jobs. 39% of software engineers hired in the past year had some sort of specialization in AI, and 35% of data engineers also said the same. AI data scientists are perhaps the most dedicated professionals in the field, and 33% of them are being snapped up by organizations these days.

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