According to the authors, “it’s time for a generative AI (genAI) reset. The initial enthusiasm and flurry of activity in 2023 is giving way to second thoughts and recalibrations as companies realise that capturing genAI’s enormous potential value is harder than expected.”
Now ask yourself who it was setting those expectations a year before. But the implications could go deeper than just adjusting for a slower pace of change than originally foreseen. The potentially transformational impact of genAI on a wide range of industry sectors and business models was deeply explored by Bhaskar Ghosh, H. James Wilson, and Tomas Castagnino who examined 19 major industries based on their level of employment, and drilled into 19,265 tasks, more than half of which they found could use generative AI as an input.
In an article published in the Harvard Business Review in December 2023, called “GenAI will change how we design jobs. Here’s how,” they explained that 44% of all working hours across industries have the potential to be impacted, rising to 72% in banking and 68% in insurance.
“For industries in the middle of the pack, like retail, travel, health, and energy, the number of working hours that generative AI could potentially transform ranged from 40% to nearly 50%. In a similar analysis across 22 job categories, we found that large language models (LLMs) will impact every category, ranging from 9% of a workday at the low end to 63% at the high end. In five of the 22 categories we examined, more than half of working hours can be transformed by LLMs,” they wrote.
While many of the early examples of genAI models going into full production were use cases at the lower end of task complexity, such as customer experience and service, the authors anticipated profound impact right through the range of knowledge work. As they explained: “Take the job of a data scientist, where 76% of all work time can be impacted by generative AI, enabling a 25% improvement in achievable productivity given the current state of technology and practice.”
Ahead of the curve, KPMG UK announced in early 2024 that it was to launch a new genAI-powered product to answer challenging tax research questions. As an example of its tasking, the tool will predict tax scenario outcomes with 90+% accuracy which employees will then review, such as working out whether a worker is employed or self-employed for tax purposes.
To do this using human effort involves searching and analysing relevant tax legislation and case law, work which genAI is able to complete much faster. The benefit expected by the firm of enabling its 3,000 tax and legal function staff with the tool is meant to be releasing them to work on more complicated or urgent issues, as well as advising clients.
Similarly, Adobe announced the introduction of genAI across its product suite with the anticipation of transforming marketing operations. “Generative AI is reshaping what we thought possible to deliver personalisation at scale across data, content and customer journeys,” said Luc Dammann, President of EMEA at Adobe. With over half (52%) of marketers already using AI, according to a study by HubSpot, and a further 45% planning to adopt it during 2024, the mood among marketers is to be empowered to create content more effectively, even if 32% don’t trust generative AI to create content that truly captures brand values.
If the most complex and the most commonplace tasks are all to be impacted by genAI, then it is worth thinking what this might do to business models which are heavily dependent currently on human skills. Notable here are marketing agencies and management consultancies, who offer little more than human capital to support their fee base, since there is relatively little unique IP they can create, other than their capability to execute strategy on behalf of clients.
Could it be that the very advocates for how efficiency gains and machine-over-human effectiveness might be the ones to experience the biggest change, resulting from client expectations that much of what they now do will be automated and therefore be delivered at a substantially lower cost?
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