But it could be argued that AI companies appear to be reducing many human workers to a mass of left-brain thinkers, and – implicitly – devaluing our more creative halves and instincts. I don't think the technology industry is anywhere near to creating a right brain, and combining that with the left to recreate what a human mind can do. But the reason why a Michelangelo or Mozart existed is because they had highly developed right brains. Our computers can master what we do on the left side of our brains very well. AI is only going to take more of those tasks, and technology will become much better at doing them.īut think about the human brain: the left lobe, and the right lobe. Taking more and more of the work that we would classify as creative? It’s an unstoppable trend. Gupta acknowledges these problems, observing: AI is increasingly doing the creative work while humans feed the machines, forcing down the earning potential of skilled, creative professionals in the process. And as previously reported (see diginomica, passim), that wave of adoption also dispels the myth that AI and other Industry 4.0 technologies will automate boring tasks, and thus free up staff to be more creative. Workers are rushing to use tools like ChatGPT, Bard, Stable Diffusion, Midjourney, and others, for day-to-day, creative tasks – sometimes to impress corporate shareholders.Īs seen in diginomica's recent interview with the CEO of start-up Private AI, this has security implications too, as more and more data is divulged to technology providers, often without IT’s knowledge or consent. But IT does understand the importance of data security.īut departments that have a niche, specialist focus are surely only one factor in AI adoption. In recent months, large-scale, popular uptake has taken place in broader business functions, such as sales, marketing, and content generation. Yet there is no IT person who can really contribute to that conversation. So, they understand three domains: chemistry, biology, and computation – including AI and machine learning. Right now, there are specialist researchers, say in pharma companies, who know AI and machine learning like the backs of their hands. Like oil, it's being consumed everywhere, so buying power is shifting to where decisions are made about how best that technology can be used. Gartner has said that the buying center is not just the technology department anymore. And as technology becomes more democratized, and as business becomes more intelligent about using it for competitive advantage, the percentage of IT department involvement is only going to decrease further. But I can tell you that is now a rapidly falling curve. There was a time when everything used to run through IT, or the CIO’s desk. That begs the question as to what percentage of AI and other new technology adoption is being driven by IT and how much is covert – based on departmental needs, or a desire to be on trend with faddy new toys? Gupta can’t quote exact figures, but says: They are not going to experiment with a technology just because it’s there! But at the moment, large-scale AI experimentation is largely being done between AI researchers and innovation units, and not by core technology functions. When a technologist implements AI in an organization, he or she will consider – far more than a business person will – issues like data privacy and intellectual property. This may create data privacy or security threats that leave IT leaders in regulators’ crosshairs as the senior responsible owners. In this case, one issue is that unwary line-of-business users may be divulging IP and other privileged data to AI companies. But with things like ChatGPT and Bard coming into the picture, the need for the technology function to start getting involved with AI adoption is only increasing.Īs seen before - with cloud computing for example -there are risks in piecemeal adoption taking place without oversight from the IT department, or from the CIO or CDO. It’s in the nature of technology that it always starts at the edge, then moves towards the center and the core. But the IT department is just not involved. For example, a lot of Life Sciences firms are starting to deploy AI, and other specialist organizations are doing a lot of experiments. That’s according to Ashish K Gupta, Head of EMEA for multi-national IT services company, HCLTech, who cautions:ĪI now is being used a lot by business stakeholders, but not by IT folks. The explosion of AI adoption is leading to a rise of shadow IT in many enterprises – unsanctioned technologies being used without IT leaders’ knowledge or permission.
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