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5 Generative AI Trends to Watch in 2025

Posted on by Bobb
5 Generative AI Trends to Watch in 2025

Generative AI is more in vogue now than ever.

This year, research in artificial intelligence was awarded a Nobel Prize, and the world’s largest technology companies have integrated artificial intelligence into as many products as possible. US government advanced AI as a driver of the creation of a clean energy economy and a strategic framework for federal spending. But what happens next in 2025?

The trend of generative artificial intelligence in the last few months of 2024 indicates increased adoption by technology companies. Meanwhile, the results are mixed on whether AI products and processes will deliver ROI for enterprise software buyers. While it’s difficult to predict how AI will continue to shape the tech industry, experts have offered predictions based on current trends.

Respondents IEEE study in September ranked AI as one of the top three technology areas that will be most important in 2025, 58% of the time. Conversely, nearly all respondents (91%) agree that 2025 will usher in a “generative AI reckoning” regarding what the technology can or should do. Expectations for generative AI are high, but the success of projects using it remains uncertain.

1. AI agents will be the next buzzword

According to my research and observations, the use of AI agents will increase dramatically in 2025.

AI agents are semi-autonomous generative AI that can combine or interact with applications to execute instructions in an unstructured environment. For example, Salesforce uses artificial intelligence agents to call sales managers. As with generative AI, the definition of an agent’s capabilities is unclear. IBM defines it like AI that can solve complex problems such as OpenAI o1. However, not all products advertised as AI agents can reason this way.

Regardless of their capabilities, AI agents and their use cases will likely be at the forefront of generative AI marketing in 2025. AI “agents” can become next stage of evolution for AI co-pilots this year. AI agents can spend time performing multi-step work on their own while their human counterpart performs a different task.

2. AI will both help and harm security services

Both attackers and cybersecurity defenders will continue to take advantage of AI in 2025. 2024 is already seeing the proliferation of AI-powered generative security products. These products can write code, detect threats, answer pressing questions, or serve as a rubber duck for brainstorming.

But generative AI may provide inaccurate information. Security professionals can spend as much time double-checking results as if they had done the work themselves. Ignoring such information may lead to broken code and even more security issues.

“As artificial intelligence tools like ChatGPT and Google Gemini become deeply integrated into business operations, the risk of accidental data exposure increases dramatically, leading to new data privacy concerns,” said Jeremy Fuchs, cybersecurity evangelist at Check Point Software Technologies. , in an email to TechRepublic. “In 2025, organizations must move quickly to implement strong controls and governance over the use of AI, ensuring that the benefits of these technologies do not come at the expense of data privacy and security.”

Generative AI models are vulnerable to attackers, just like any other software, especially through jailbreak attacks.

“The growing role of artificial intelligence in cybercrime is undeniable,” Fuchs explained. “By 2025, AI will increase not only the scale of attacks, but also their sophistication. Phishing attacks will be harder to detect as AI is constantly learning and adapting.”

Generative AI could make traditional methods of identifying phishing emails (bad grammar or unexpected messages) obsolete. The safety of misinformation will become more important as AI-generated video, audio and text spread. As a result, security teams have to adapt to both usage and protection against generative AI — just as they have adapted to other significant changes in business technology, such as the large-scale move to the cloud.

3. Companies will evaluate whether AI provides a return on investment.

“The pendulum has swung from ‘new AI innovation at any cost’ to a deafening need to prove ROI in boardrooms around the world,” Uzi Dvir, global CIO of digital adoption platform company WalkMe, said in an email. “Similarly, employees are wondering whether it’s worth the time and effort to figure out how to use these new technologies for their specific tasks.”

Organizations are trying to determine Does generative AI add value? and for which use cases it might make the most difference. Organizations implementing AI often face high costs and unclear goals. It can be difficult to quantify the benefits of using generative AI, where those benefits occur, and what to compare them to.

This problem is a side effect of the integration of generative AI into many other applications. This leads some decision makers to question whether generative AI additions actually add value to these applications. Levels of artificial intelligence can be expensive, and over the next year, more companies are expected to rigorously test and sometimes discard features that don’t deliver results.

Many companies that widely implement generative artificial intelligence are seeing success. On your own 3rd Quarter Earnings ReportGoogle attributed this result to its AI infrastructure and products such as AI reviews. However, Meta reported that AI could significantly improve capital costseven though the number of users is declining.

WATCH: Google Cloud unveils sixth generation AI accelerator Trillium.

4. AI will have a big impact on scientific research

In addition to its impact on enterprise productivity, modern artificial intelligence has undergone significant changes in science.

Four 2024 Nobel Prize winners have used AI:

  • The winners of the competition were Demis Hassabis and John Jumper from Google DeepMind. Nobel Prize in Chemistry for protein structure prediction using AlphaFold2.
  • John J. Hopfield and Geoffrey Hinton won Nobel Prize in Physics for their many years of work developing neural networks.

On October 31 and November 1, a summit was held at the White House on the issue use of AI in life scienceshighlighting how artificial intelligence can solve complex problems while making an impact on the world. This trend is likely to continue into next year as generative AI models grow and improve.

5. AI-powered environmental tools do not offset energy costs.

Energy efficiency is another buzzword in the artificial intelligence space.

But for every use case where AI can help predict weather conditions or optimize energy use, there is another story about the environmental costs of construction data centers necessary to run generative AI. Such construction requires enormous amounts of electricity and water, and rising global temperatures are only exacerbating the problem. It is unlikely that balance will be achieved in this large-scale problem.

However, businesses expect to see companies touting dubious and sincere claims about energy savings and environmental friendliness of AI. Consider resource usage related to your organization’s AI strategy.

What are the most popular generative AI products?

The most famous generative AI products are:

What is the most advanced generative AI?

Various tests have been proposed as potential criteria to determine the most advanced generative AI. Some organizations evaluate their models against human education criteria, such as the International Mathematics Olympiad or Codeforce competitions.

Other assessments, such as Measuring Language Comprehension under Multitasking, were created specifically for generative AI. Google’s Gemini Ultra, China Mobile’s Jiutian and OpenAI’s GPT-4o take the top spots. MMLU Leaderboard Today.