How will generative AI reshape the enterprise?

10 ways GenAI is reshaping the enterprise

Enterprise adoption of GenAI varies from one organization to the next, as some charge ahead with full-scale deployments while others cautiously test proofs of concept.

Moreover, organizations -- regardless of where they are on their AI journey -- are contending with challenges and risks that could slow, stymie or derail their AI initiatives.

By all accounts, organizations must have the right amount of data at the right level of quality, as well as appropriate levels of human oversight based on the use case to ensure AI outputs are accurate, complete and fair. They need ways to explain and verify the results of their AI, too, in part to catch and correct any unintended biases, AI hallucinations and other possible problematic behaviors of their AI systems.

Organizations must address ethical questions and compliance requirements as they move forward to make sure they're getting benefits and minimizing risks. They also should rework processes to integrate AI alongside their human employees in ways that deliver the most benefits to workers, customers and the organization.

Despite such challenges, organizations are demonstrating successful transformations using GenAI. Here are 10 ways GenAI is reshaping the enterprise.

1. Improving and automating customer service

AI has aided the customer service function for years, but GenAI creates a more natural interaction between humans and machines.

When used to bolster automated customer support via chatbots, GenAI engages customers using natural language while accessing and analyzing data to deliver fast and accurate answers to questions, said Arpita Soni, a senior member of the professional association IEEE and a senior project manager at Infosys Technologies.

When used to support customer service agents, GenAI is a powerful assistant that guides human agents through conversations with customers and provides them with the right information to service those customers, said Jim Rowan, a principal and head of AI at professional services firm Deloitte.

This use of GenAI for customer service not only boosts productivity and efficiency, but it also helps train and improve real-life customer service representatives with the GenAI-generated guidance acting like an assistant with years of experience.

In a December 2024 survey, research firm Gartner found that 85% of customer service leaders will explore or pilot customer-facing conversational GenAI systems in 2025.

But Gartner also predicted that the most successful organizations will use GenAI in customer service to support -- not replace -- humans. "Generative AI promises a new solution to an age-old problem: costly assisted service. We expect that customer service and support leaders who leverage generative AI to enable human contact will be more successful than those who leverage it to reduce human contact by eliminating assisted service," researchers noted in the report "Strategy and Leadership Predictions for Service and Support Leaders in 2024."

This conclusion mirrors findings from multiple reports studying GenAI use in the enterprise, which stated AI will work alongside and not in place of people.

2. Enabling information retrieval and knowledge management

GenAI shines at searching and analyzing unstructured and structured data. This makes it an invaluable resource for finding and retrieving information from documents and other records and then presenting it in highly useful and actionable formats, said Christine Livingston, a managing director and AI practice leader at global consulting firm Protiviti.

"Knowledge management (KM) is experiencing an exciting transformation fueled by the merging of generative AI, human-centered practices, and the evolving landscape of hybrid work," wrote Forrester Research principal analyst Julie Mohr in a Nov. 27, 2024, blog.

She went on to state that GenAI "is set to play a game-changing role, but its true potential will shine through when combined with a focus on human-centered practices." Mohr concluded that although "AI can do a lot to streamline processes and boost efficiency, there's no replacing the unique qualities of human creativity, empathy, and teamwork. The real challenge is finding ways to use AI that keep people at the heart of what we do."

3. Aiding supply chain management

With its ability to find, retrieve and analyze data, the technology is helping organizations improve supply chain management.

Multiple reports described how GenAI can cull through historical, internal and external data to understand the context of what's happening. This lets the technology predict demand, optimize inventory levels, identify potential risks such as possible disruptions, optimize logistics such as transportation routes, ensure regulatory compliance and automate tasks.

"It is helping to know how many projects there are, what resources are available to meet project needs, and how much is needed," Soni said.

These GenAI-enabled improvements save money and increase productivity; they can also boost environmental sustainability, particularly if the GenAI tool is prompted to consider sustainability as part of its analysis.

In a May 2024 report, "The State of AI in Early 2024: GenAI Adoption Spikes and Starts to Generate Value," global management consulting firm McKinsey & Co. looked at the value created by GenAI's use by business function. The report found respondents "most commonly report meaningful revenue increases (of more than 5 percent) in supply chain and inventory management."

4. Creating content

GenAI's ability to generate content -- text, audio and visual -- is one of the technology's best-known capabilities. Organizations and their employees use GenAI for everyday tasks, such as drafting emails and presentations, and for high-value business needs like creating marketing campaigns and commercials, said Bill Wong, an AI research fellow who leads AI and data analytics research at Info-Tech Research Group.

A September 2024 report from Enterprise Strategy Group found that 35% of respondents cited content creation as a GenAI benefit.

5. Producing computer code

GenAI also generates computer code, user requirements and related documentation, resulting in significant time savings for programmers, Rowan said. The technology brings coding capabilities to nontechnologists, enabling them to bring software features and functions to life quickly and nearly automatically, further speeding the time between ideation to delivery of code.

In its November 2023 report titled "The Art of Software: The New Route to Value Creation Across Industries," Capgemini Research Institute estimated that 37% of code will be generated with assistance from GenAI by 2026.

6. Boosting employee productivity with AI assistants

As employees ramp up their use of GenAI and optimize its capabilities, they can use the technology to perform a greater number of tasks, creating even more significant productivity gains for their organizations, Wong said.

The report from Enterprise Strategy Group found increased productivity as the No. 1 benefit from GenAI, with 60% of respondents stating GenAI delivered value on that front. That's because GenAI enables organizations to do more work, faster and with fewer resources.

That's evident in the GenAI use cases Wong and others cited, as AI-powered assistants help programmers, customer service reps, marketing creatives, operations professionals and others handle tasks that previously only humans could perform.

7. Identifying opportunities for improvement

Organizations can use GenAI to improve and automate tasks and processes; additionally, they can use GenAI "to find opportunities, to find processes that can be automated," Soni said.

Rowan said organizations are in the early stages of using GenAI in this way, but they're increasingly employing it to "say this is the outcome we want and let's work backwards to have AI reimagine the process."

8. Jumpstarting research and development activities

Although its use in research and development is still mostly experimental, Livingston said GenAI has already shown promise in helping organizations jumpstart R&D activities. The technology can find promising opportunities to explore, identify which opportunities have the most potential and then iterate through different options very quickly.

Some companies are making huge bets with huge amounts of investments for these new patterns of discovery [with GenAI]. But I think the efficacy and accuracy of some of the output is still very much being evaluated.

Much of this experimentation is happening in drug discovery and the materials science space, where companies are using GenAI to find, investigate and explore new compounds, Livingston said.

"Some companies are making huge bets with huge amounts of investments for these new patterns of discovery [with GenAI]," she said. "But I think the efficacy and accuracy of some of the output is still very much being evaluated."

Others had a similar take. In a June 2024 report on GenAI in R&D, Gartner concluded that "GenAI promises significant productivity, efficiency and cycle time improvements in R&D processes, even though the technology is still nascent."

9. Finding new ways to differentiate and to generate new revenue

Organizations are using GenAI to innovate -- whether that's to create new products and services or to find new ways to differentiate themselves in the market, Wong said. They might use GenAI to identify such opportunities, or they might use GenAI as the basis for their innovations, products and services.

Wong noted that few organizations are advanced enough in their GenAI use to do this work, adding that those who use GenAI in this manner are leading the way for others to follow.

He pointed to J.P. Morgan as an example of a leader in this space. In July 2024, the firm announced it had launched Quest IndexGPT, a set of stock indices that use GPT-4 to generate keywords related to specific investment topics. The system then finds articles with these keywords and identifies companies with relevant stocks for investors.

10. Automating more decision-making

Organizations are using GenAI to bring the power of analytics to more workers throughout the organization, Livingston said -- a move that gives everyone the ability to make data-driven decisions.

"A lot of the analytics in organizations requires users to have an understanding of the data they're looking at," she said. "But organizations that have GenAI on top of [their data analytics infrastructure] to make that data conversational are lowering the barriers to understanding, interpreting and acting on that data. That can help unlock data-driven decision-making instantly because [any employee] could then chat with the data. It enables a new level of analytics and data-driven decision-making."

GenAI is also a building component for agentic AI systems to support even more automated decision-making. Agentic AI systems can act autonomously to solve multistep problems in real time, determine the right actions to take and then take those actions to accomplish the desired outcome. Agentic AI is considered by many to be the next step in intelligent systems.

Mary K. Pratt is an award-winning freelance journalist with a focus on covering enterprise IT and cybersecurity management.