If you go back in time, you’ll discover that this isn’t the first AI hype cycle since the technology’s inception in the 1950s. But this time around, significant advances and the rise of deep learning have pushed AI past the point of no return. From AI-driven enterprise-level software to the increased democratization of generative AI tools like ChatGPT and Dall-E, we’re already experiencing AI’s deep impact and realizing its immense value. Like the internet, at a certain point, AI too will become ubiquitous. But right now, we’re only scratching the surface of what AI can do for business.
In Splunk’s Executive Predictions 2024, my colleagues and I predict that although AI will enhance the productivity of workers, significant business impact won’t be immediate. That’s because the technology is still maturing, and business leaders are still determining the best ways to incorporate it into their workflows.
Prediction: AI will drive valuable, incremental gains in efficiency and productivity in the short term — but business leaders will have to see it to believe it. Step changes in business impact are still 12 to 24 months out.
According to McKinsey, “Generative AI will automate half of today’s work activities between 2030 and 2060.” And as the technology continues to develop, more companies are implementing it into enterprise-level software, such as the AI-driven virtual assistant Microsoft 365 Copilot.
In the cybersecurity world, oftentimes, teams are stretched too thin and can’t keep pace with the growing number of cyber risks that threaten their organizations. In our CISO Report, 86% of CISOs surveyed believe that generative AI will alleviate skills gaps and talent shortages they have on their security teams, supplementing staff by performing some of the more time-consuming functions. In addition, CISOs are looking to leverage generative AI as an educational tool for their staff and to bolster their organization’s security posture.
But AI isn’t out to take anyone’s job. In fact, it’s fostering new ones. As McKinsey notes: “Roles in prompt engineering have recently emerged, as the need for that skill set rises alongside gen AI adoption.” Already, 46% of CISOs plan on getting their security teams up to speed on effective prompt engineering, per Splunk’s CISO Report.
Generative AI has changed the software development process, and we’re seeing more developers use the application to initiate new code and as a form of pair programming. That’s why embracing the technology now is critical. AI is here to stay. To help future-proof your organization, the more experience your workforce has using generative AI now, the better off they will be later on. In the future, AI will be seen as just another tool in a developer’s work belt, and knowing how to use it will become a basic job requirement.
So why are business leaders hesitant to implement generative AI applications?
For starters, it can be very expensive. Not every business has the infrastructure, talent pool or budget to implement AI at scale to the extent that it’s currently useful. Total AI implementation costs can vary, depending on the use case, as well as whether or not an organization buys or builds its AI solution. For example, Microsoft 365 Copilot only costs $30 per user per month. On the other hand, if an organization wants to build copilot capabilities themselves, that cost skyrockets. Either way, both “build” and “buy” options encompass many factors like software, workforce and training/maintenance costs, as well as team/company size and solution complexity. Therefore, AI implementation could run anywhere from a few thousand dollars to a few million. (Last year alone, OpenAI burned through $540M developing ChatGPT). That’s why any business leader looking into investing in AI today needs to evaluate its current benefits and weigh that against their timeline for expected ROI.
There are quality concerns as well. Making headlines recently is the issue of AI hallucination. An excellent example of this problem is when journalists asked ChatGPT what date The New York Times first reported on AI, the platform cited a bogus article from 1956. For the time being, the problem cannot be eliminated, causing business leaders to slow down or potentially re-evaluate their use of the technology, particularly when it comes to critical cybersecurity applications.
In addition to cost and quality, there’s the issue of security and privacy. Many companies, rightfully so, do not allow employees to use generative AI tools because of concerns over how data fed into large language models (LLMs) are used and stored. Organizations must ensure the protection of their IP, and until there is clear oversight and regulation on how best to achieve this, many business leaders don’t want to take the risk.
Striking AI gold
Regardless, next year, we will see more AI use cases emerge. In fact, Splunk Chief Strategy Officer Ammar Maraqa believes that much of the hype surrounding AI this year will be concentrated on new players. “We are in an AI Gold Rush, where everyone is building or using these LLMs and figuring out how to apply them to novel use cases,” Maraqa says. “In 2024, we are going to see even more investment dollars funding these opportunities.” But he warns that we must be careful. “The market is unedited right now in its use of AI,” says Maraqa. “It’s being fundamentally applied to everything because we don't yet know what the limitations or killer apps are — or where the highest value lies.”
Although we can safely predict that 2024 will not be the year of AI singularity, Splunk expects the technology to advance even further this year, particularly when it comes to automation and human assistance applications. One day, business leaders will look back on this nascent stage of AI and view it as an inflection point for productivity and efficiency. Exponential growth is coming: In 1993, only 1% of information flowing through two-way telecommunications occurred on the internet. By 2007, that number exploded to 97%. It’s clear to see that AI adoption will follow that trajectory.
To find out what other predictions will shape the coming years, read Splunk’s 2024 Executive Predictions. And check out our AI Philosophy Powering Digital Resilience e-book to learn Splunk’s strategy for AI in our products, as well as guidance on using AI responsibly.
