Gartner sees generative AI as 'top priority' for C-suite
Excitement over generative AI is reaching fever pitch, with Gartner forecasting rapid growth for enterprise uptake.
October 12, 2023
Excitement over generative AI is reaching fever pitch, with Gartner forecasting rapid growth for enterprise uptake.
The analyst firm has predicted that by 2026, more than 80% of enterprises will have used genAI application programming interfaces (APIs) or models, and/or deployed genAI-enabled applications in production environments. That compares to less than 5% in 2023.
“Generative AI has become a top priority for the C-suite and has sparked tremendous innovation in new tools beyond foundation models,” noted Arun Chandrasekaran, distinguished VP analyst at Gartner. “Demand is increasing for generative AI in many industries, such as healthcare, life sciences, legal, financial services and the public sector.”
Gartner said three innovations in particular are expected to have a huge impact on enterprises over the next decade.
First up is the one most industry observers are familiar with – foundation models (FMs). These are the general-purpose cousins of the LLMs, which by comparison are trained to carry out specific conversational tasks, like being a chatbot, for example.
“Foundation models will advance digital transformation within the enterprise by improving workforce productivity, automating and enhancing customer experience and enabling cost-effective creation of new products and services,” said Chandrasekaran.
Then there are genAI-enabled applications, Gartner said, which will do clever things like offer prompts to help employees complete tasks that might otherwise have been the preserve of specialists.
The third innovation identified by Gartner is AI trust, risk and security management (TRiM), which aims to head off any unintended negative consequences of genAI usage, such as unethical or inaccurate recommendations.
“Organisations that do not consistently manage AI risks are exponentially inclined to experience adverse outcomes, such as project failures and breaches,” said Chandrasekaran. “Inaccurate, unethical or unintended AI outcomes, process errors and interference from malicious actors can result in security failures, financial and reputational loss or liability, and social harm.”
The telecoms and tech industries are only too willing to help enterprises harness these genAI innovations, spinning up their own AI businesses to help customers revolutionise both back-office functions as well as front-end processes like customer relationship management (CRM).
Recent developments include Google, which last week revealed that its latest range of Pixel smartphones come with a version of Google Assistant that incorporates its AI chatbot, Bard.
In late September, France-based telecoms group Iliad announced it will deploy an Nvidia supercomputer, which will power a range of B2B AI services on offer from its Scaleway cloud division.
Just days before Iliad’s big announcement, SK Telecom announced its three-pronged strategy for capitalising on enterprise AI demand. Under the strategy, it will triple its AI investments in the hopes of generating $18.5 billion of revenue from AI-related services by 2028.
It’s an ambitious target, but if Gartner’s prediction is accurate, it could just be an achievable one.
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