80% of companies will have integrated AI by 2026, according to Gartner

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80% of companies will have integrated AI by 2026, according to Gartner

Since the release of ChatGPT almost a year ago, generative AI has been booming, with companies developing or adopting AI models. A new report from Gartner shows that growth will only increase in the coming years.

The research firm predicts that 80% of companies will have used APIs (application programming interfaces) or generative AI models, or developed their own models by 2026.

This means that in just three years, the number of companies adopting or creating generative AI models will have increased sixteen-fold since, according to Gartner data, less than 5% of companies did so in 2023.

“Generative AI has become a top priority and has sparked tremendous innovation with new tools,” said Arun Chandrasekaran, analyst at Gartner.

The research firm has defined some of the innovations that are expected to have a massive impact on organizations over the next ten years, including :

  • Applications based on generative AI
  • The basic models of AI
  • And the management of trust, risk and security of AI (AI TRiSM – Trust, Risk, and Security Management)

Applications based on generative AI

Applications based on generative AI are applications that exploit generative AI to accomplish a specific task. ChatGPT is an example of an AI-based generative application, since it uses AI to synthesize your text prompts and produce a response.

Organizations can adopt these applications to facilitate the work of employees or to offer customers experiences that improve their services.

“The most common model today is text-to-X, which democratizes employee access to what used to be specialized tasks, through prompt engineering using natural language,” Chandrasekaran said in the report.

A prime example of this is the growing number of consulting companies that are adopting or developing their own AI models to make it easier for clients to find the resources they need in the company’s extensive databases.

The problem with these applications is that they are prone to hallucinations and inaccurate answers that make their reliability doubtful.

The basic models of AI

The basic models refer to the machine learning models that underlie generative AI applications, for example, what GPT is to ChatGPT.

These basic models are trained on large amounts of data and are used to power different applications capable of performing a wide variety of tasks.

Gartner has placed basic models at the top of the exaggerated expectations of the Hype cycle, predicting that by 2027 they will be the basis of 60% of natural language processing (NLP) use cases.

Hype Cycle for Generative AI, 2023


“Technology leaders should start with models with high accuracy, ones that have significant ecosystem support and have adequate corporate safeguards around security and privacy,” Chandrasekaran said.

AI TRiSM – Trust, Risk, and Security Management

Finally, AI TRiSM designates all the solutions to solve the problems related to generative AI models and to guarantee the success of their deployment.

The risks that weigh on generative AI models are reliability, misinformation, bias, privacy protection and fairness.

If not handled properly, these problems can be particularly detrimental to organizations, as they risk leading to the leakage of sensitive data and the dissemination of false information throughout the organization.

“Organizations that do not consistently manage AI risks are prone to experiencing negative outcomes, such as project failures and breaches,” Mr Chandrasekaran said.

AI TRiSM is therefore crucial for organizations in order to minimize these risks and protect the members of their organization.

Source: “ZDNet.com “

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