AI enterprise future

Following its widespread introduction into enterprise environments in 2023, the adoption of enterprise AI is expected to be much more significant and intentional in 2024.

Carter Busse, CIO at automation platform provider Workato, says that 2023 proved to be the year of AI enterprise experimentation, and 2024 will be the year of building infrastructure and setting a foundation for future innovation with AI.” The economic and geopolitical climate is pushing business leaders to the forefront of innovation whether they want to be there or not – they know they need to make decisions quicker, faster, and more efficiently than ever before,” he says.

“Business leaders know they need to use generative AI but are unsure how to get there. After a year of experimentation, 2024 will be about building infrastructure and setting the foundation for realizing generative AI use cases across the enterprise,” he continued.

“As we reflect on the generative AI landscape in 2023, it’s evident that numerous companies found themselves entangled in the noise surrounding this technology. Looking ahead to 2024, a discernible shift is anticipated, with companies focusing on identifying practical applications of generative AI that bring tangible value to business operations, steering away from mere novelty,” says Scott Richards, SVP of Software Engineering at OpenText.

No doubt. And many other experts shared their views of AI and the year ahead:

GenAI Brings Significant Changes to Enterprise Analytics

OpenText’s Richards predicts a considerable impact on generative AI and the business intelligence market in the year ahead. He stated that traditional business intelligence (BI) vendors must transform their offerings. “To sustain competitiveness, these vendors must integrate generative AI capabilities into their tools, ushering in a new era of more potent and automated BI solutions. This evolution promises to deliver enhanced insights and foster a more intuitive user experience,” he says.

He adds that the ramifications of this shift will be manifold, including GenAI’s potential to autonomously generate insights and narratives from data, potentially replacing or complementing manual efforts in report and dashboard creation. This diminishes the necessity for human intervention in the generation of insights. “The insights produced may unveil previously undiscovered relationships between organizational business processes, paving the way for newfound efficiencies. Thirdly, generative AI can play a pivotal role in automating data cleansing and preparation, enhancing accessibility for reporting and predictive analysis,” he added.

Richards also predicts considerable analytics convergence. Today, analytics is performed on segmented platforms that separate traditional business intelligence, Internet of Things analytics, AIOps, predictive analytics and generative AI. The separation often causes disparate data siloes to form, increasing costs to store replicated data and security concerns about its handling. “Single pane of glass analytics unifies data or interfaces across several different sources and presents them in a single view.  It allows for a wide variety of analytical forms to run, handling the needs of a large portion of an enterprise. Mechanisms will be put into place to allow these disparate workloads to run in their workspace without impacting different teams. Going forward, analytics users will seek a way to look at various data sources in a single place regardless of analytical style,” he says.

Expect a Customer and Business AI Gap

There’s a potential gap brewing between how much AI companies are going to give to customers and how much AI their customers may be willing to tolerate. “One of the biggest trends in 2024 will be what we’re calling “The AI Gap”: the clear divide emerging between consumers and business leaders when it comes to adoption, enthusiasm, and education around AI,” says Ruth Zive, chief marketing officer at LivePerson.

According to LivePerson’s 2024 State of Customer Conversations report, 91% of business leaders feel optimistic about using AI to engage with customers, but 50% of consumers say the same. Last year, 62% of consumers felt positive about engaging with AI. “Similarly, when asked to choose between speaking with a human or a bot to handle everyday tasks, business leaders overestimate how many consumers would choose the bot by around 19% for each task. We’re in a world where AI dreams and consumer realities are colliding,” Zive says.

“This setback in consumer sentiment contrasts with business leaders’ excitement and, paradoxically, is emerging as businesses double down on AI and automation. Here’s the good news: 2 out of every three consumers expect how they work with businesses to improve over the next five years thanks to AI. With their expectations running longer than business leaders, brands that put together engaging, helpful AI-powered experiences “ahead of schedule” will have a leg up over their competition,” Zive says.

Despite consumer skepticism, Zive doesn’t expect brands to slow down when using AI, as it is already helping them reduce wait times, assist agents, and reduce costs. However, brands will only truly gain the total ROI on AI if they find ways to bridge the AI gap with their customers. What does that bridge look like? It’s about using AI to understand better what customers are telling you, empower your agents, save time by speeding up resolutions on the channels customers prefer, and learn from all of the above to get even better.

Big Impact on Software Development

Experts expect AI to cut software development time dramatically. Traditional development is time-consuming and requires significant expertise, but with AI and ML integration, manual coding and testing will become a thing of the past, explains Mohan Atreya, SVP of product and solutions at Rafay Systems. “These technologies excel at generating code and drastically reduce manual work. They also analyze data comprehensively, pinpoint inefficiencies, and recommend efficient resource management. This shift allows businesses to redirect human resources towards strategic goals, fostering innovation and growth,” Atreya says. Atreya expects organizations to experience enhanced efficiency, reduced costs, and seamless collaboration between human expertise and AI.

The productivity these tools will deliver could not come at a better time as we desperately need more developers. The U.S. government is projecting 25% job growth from 2022 to 2032 for software developers, quality assurance analysts and testers. With a talent shortage to fill these roles, AI-powered software tools will dramatically make the developers that organizations already have on staff more efficient and begin to close that talent gap, explains Peter Guagenti, president and CMO of Tabnine.

GenAI Within Enterprise Shadows

While Shadow IT has been around since the advent of the iPhone and other more modern smartphones and tablets, it’s grown to encompass not just devices but all sorts of consumer consumable technology appearing in the enterprise. With little more necessary than an email address and a credit card, anyone can deploy cloud infrastructure or a cloud application. The same is now true for GenAI.

“With the unsanctioned use of generative AI services rapidly growing within the enterprise, that risk has now expanded to exposure of intellectual property and customer data being exposed outside of your organization. In 2024, we can expect businesses without strong AI compliance policies and visibility into the tools being used by their employees to experience higher rates of PII exposure. I also expect to see at least a couple of incidents of proprietary source code being inadvertently used to train AI models not under IT’s control. My hope is that this will be a significant wake-up call for tech teams and business leaders at large about the urgent need for a proactive, enforced plan around responsible generative AI use,” predicts Heath Thompson, president and general manager at Quest Software.

Disruptions Within Specific Industries Continue

In 2024, GenAI is expected to continue to bring a significant impact on various vertical markets. According to industry experts, GenAI will also increasingly become commoditized and embedded in multiple applications, leading to a race among software providers to monetize GenAI while controlling its negative aspects. Because companies better understand how to use GenAI functionally, they will begin to leverage it more competitively.

Mike Haney, CIO at Battelle, believes the year ahead will witness even greater acceleration of innovative use cases as the world becomes more familiar with what these tools can do for us. I’d expect advancements in the algorithms and computational power and tools that can ensure transparency, accountability, and trust in AI systems that will lead to a completely ubiquitous use worldwide.”

“Business leaders will warm up to the technology and coupling it with automation to drive innovation further. Businesses will move beyond thinking about tasks individually and evolve to focus on automating end-to-end processes,” concludes Workato’s Busse.