AI investments: When will we see returns?

The rise of Artificial Intelligence (AI) has been remarkable. In just a couple of years, there’s been an explosion in AI technologies that is transforming all industries. The launch of ChatGPT and other generative AI tools has plugged AI into the spotlight.

The AI boom has triggered a gold rush, with investors pouring money into AI startups, often at jaw-dropping valuations. It’s not just the tech giants either; businesses across all sectors are jumping on the AI bandwagon, hoping to harness its power to streamline operations, crunch massive datasets and gain a competitive edge.

Yet, as the dust begins to settle on the initial AI frenzy, investors and analysts are starting to ask some tough questions about the impact of AI on companies’ bottom lines. So, when will these significant investments start to pay-off?

The AI investment landscape

The global AI market, valued at approximately $200 billion in 2023, is projected to grow a staggering 20% annually, reaching $2 trillion by 2023, potentially. Companies across various sectors are allocating vast resources to develop and implement AI technologies to support business goals and boost efficiency.

In fact, it’s estimated that investors are funneling about $60 billion per year into AI model development, an amount that could create 12,000 products on the scale of ChatGPT. Moreover, tech giants alone are expected to pour $210 billion into AI-related capital expenditures in 2024.

This level of investment underscores the industry’s strong belief in AI’s potential to revolutionise work and society. Many companies are willing to accept short-term costs in pursuit of long-term gains.

Early signs of return

While many AI investments have yet to prove value and ROI, there are encouraging indicators from early adopters. Some companies have reported tangible benefits from AI investments in areas such as content recommendation and advertising tools, contributing to year-over-year revenue increases.

Others have noted significant enterprise savings from internal use of AI investments.

However, despite these promising signs the road ahead is complex. Recent market volatility experienced by companies which have heavily invested into AI reflects ongoing concerns around the timeline for profitability in the sector.

Navigating challenges and regulatory considerations

One of the most pressing issues is the sheer cost associated with AI development and implementation. Companies are finding that creating, deploying and maintaining AI systems requires substantial, ongoing investment. It’s not just about the initial plans for technology and talent, there’s also the continuous need for computing power, data storage and security measures. The costs can quickly add up, eating into potential profits and extending timelines for tangible returns.

Moreover, many companies are still in the experimental phase with AI, which brings its own set of challenges. They’re grappling with questions about how to best leverage AI within their specific business contexts. This experimentation, while necessary, can be costly and time consuming. It also means that many organisations have yet to find the perfect fit for AI within their operations, further delaying the pay-offs.

And of course there are ongoing challenges to manage around data security, privacy, accuracy, and potential biases.

In the Mergers and Acquisitions (M&A) industry, for instance, dealmakers are taking a more cautious approach with the technology. In a survey of over 500 global dealmakers, Datasite, which annually facilitates 15,000 new global deals, found that 60% of M&A professionals reported low or experimental adoption within their organisations.

Moreover, the M&A industry, like many other industries, is cautious to implement the technology without more robust governance and regulation. Our research indicates that while 42% of M&A professionals view increased productivity as a primary benefit of generative AI in their business, many also advocate for some form of regulation to address these ongoing concerns.

Future outlook

Despite these challenges, the potential benefits of AI are clear. In M&A, for example, AI can transform due diligence processes, reducing weeks of work into shorter time frames. This not only saves time but also minimises human error and improves regulatory compliance.

As a result, we anticipate increased AI-related M&A activity, potentially leading to some consolidation in the AI subsector. This is likely to be fuelled by startups that may be acquired for their AI capabilities, talent or both.

In fact, the generative AI boom, coupled with easing financing conditions, is creating a robust TMT market. Global TMT sell-side deal kickoffs on Datasite were up 12% globally, and 14% in EMEA in the first half. Since these are deals at their inception, rather than announced, it provides a good indication of what’s to come in the next six to nine months.

The path to pay-off

Ultimately, the returns will be in the long-term. The companies that will see the greatest pay-off from their AI investments will be those that can effectively integrate AI into their core business processes, address security and ethical concerns and deliver real value to their customers.

Successful companies will focus on providing clear use cases for AI, hiring the right talent to manage and implement the technology and ensure robust security measures are in place. By providing this solid foundation, companies can create an environment where AI investments are more likely to thrive and generate substantial returns.