The speed at which Artificial Intelligence (AI) continues to expand is unprecedented, particularly since GenAI catapulted into the market in 2022. Today AI works at a much faster pace than human output, which is what makes this technology so appealing to leaders who are focused on streamlining operations, productivity gains and cost efficiencies. But for those who thought that AI was a more recent phenomenon, you are mistaken, cybersecurity has leveraged AI for decades, and the trend has accelerated in recent years. AI is now found in a plethora of cybersecurity tools, helping to enhance threat detection, response, and overall system security and has a long history stretching back to the 1950s.

The possibilities of thinking machines

In 1956 John McCarthy, a professor of mathematics at Dartmouth College, invited a small group of researchers to participate in a summer-long workshop focused on investigating the possibility of ‘thinking machines’, and they were consequently credited with founding the field of AI. Subsequently many studies and projects took place throughout the 60s, 70s and 80s, but it wasn’t until progress in the late 90s that the field gained substantially more R&D funding to make significant leaps forward, enabling the first driverless cars to become a reality.

It was around this time that IBM’s computer system, Deep Blue, beat the world chess champion, Gary Kasparov, in 19 moves during the final game.  While Deep Blue didn’t have the functionality of today’s generative AI, it could process far more quickly than a human could.

But it was arguably when Apple launched Siri in 2010 and Amazon launched Alexa in 2014, new virtual assistants that had natural language processing (NLP) capabilities that could understand a spoken question and respond with an answer, that AI entered more fully into the consumer consciousness. Both Siri and Alexa are based on AI, ML, and NLP technologies, and their backends are continuously improving through frequent updates over the cloud. Then, of course, we had the OpenAI launch of ChatGPT in 2022 and the rest, as they say, is history.

Where reality doesn’t match expectations

However, while GenAI receives much of the hype when it comes to AI, the technology has yet to deliver on its anticipated business value for most organizations. The hype surrounding GenAI can cause AI leaders to struggle to identify strong use cases, it unnecessarily increases complexity and increases the potential for failure.

According to Gartner, GenAI has passed the Peak of Inflated Expectations in its eponymous Hype Cycle and by the end of 2024, value will be derived from projects based on familiar AI techniques, either stand-alone or in combination with GenAI, that have standardized processes to aid implementation.

An AI reset is underway

Without a doubt, technology and security teams experimented in 2024 and learned some valuable lessons. There were AI pilots running in all corners of the enterprise, while macro-economic market trends sent some long-held strategies askew throughout the year. As we look forward to 2025, a new phase of AI will begin as leaders consider how they turn lessons learned into profit. Those who succeed will be deliberate, balancing short-term wins with longer-term foundational improvements.

In 2025, some experimentation will certainly continue, but as mentioned above, technology and security leaders will focus on putting lessons learned into practice. However, the intense pressure to show ROI after a period of pilots and experimentation will drive some leaders to rush deployments and make premature decisions that could cost them dearly.

Leaders are realizing that ROI from investments will take longer than they anticipated and are shifting toward pragmatically delivering ROI over time. In Forrester’s Q2 AI Pulse Survey, 2024, 49% of U.S. generative AI decisionmakers said their organization expects ROI on AI investments within one to three years, and 44% said within three to five years. Impatience with AI ROI could prompt enterprises to prematurely scale back investments, which could put them at a longer-term disadvantage. Instead, I would encourage AI leaders to establish a solid strategy aligned to their business model and aspirations. 

We saw a similar trend with cybersecurity automation where, over a three-to-four-year period, it moved along the Gartner Hype Cycle and landed on specific use cases where value was to be found and trust in outcomes had increased.

Future waves of AI will have their own cycle

This is where I got to in my last article when I talked about the next wave of AI potentially being “SynthAI”. To date, generative AI applications have overwhelmingly focused on the divergence of information. That is, they create new content based on a set of instructions. In future waves of AI there will be more applications of AI to converge information. In other words, they will show us less – but more relevant – content by synthesizing the information available. SynthAI will improve the quality and speed of decision making, if not actually make the decision itself. The most obvious application here is to summarize high volumes of information that humans could never digest themselves directly. The real value of SynthAI in the future will be in helping humans make better decisions, faster.

The use cases that will benefit most from SynthAI will be when there is a high volume of data, such that it’s not pragmatic for a human to manually sift through all the information. And where there is a high signal-to-noise ratio, such that the themes or insights are not obvious and consistent.

Ultimately the potential for how AI may change the way we work is endless, but we are still a way off from this and careful planning and consideration, after a couple of years of experimentation, is what is needed.  I certainly believe that GenAI in B2B applications needs to evolve beyond creating more content, to SynthAI that enables us to do our work better and faster. But I would advise on AI with caution or AI with guardrails and a clear focus on how to return a multi-year ROI in 2025 and beyond.