When the going gets tough for businesses, the emboldened are turning to artificial intelligence (AI) and machine learning (ML) to move ahead. As more companies rely on these technologies to operate, industry experts expect AI will add trillions of dollars to the global economy by the next decade.
“Companies that fail to adopt this technology and leverage it to the fullest extent possible are certain to fall behind and eventually become irrelevant,” said Martin Ford, author of Rule of the Robots: How AI Will Transform Everything.
“By contrast, companies who act immediately and begin to develop an AI strategy [have the chance to create] competitive advantage. Recent analyses from McKinsey and PwC estimate that AI will add as much as $13 trillion to the global economy by 2030. This likely explains why there are massive investments pouring into AI… both internally among corporations and in the VC space.”
Benefits of AI and Machine Learning Solutions for Businesses
The world’s most valuable resource is now data, not oil, according to The Economist. To manage the growing amounts of data, businesses are turning to AI and ML technologies as indispensable business tools to stay competitive.
Forrester even says AI and ML are foundational for any modern enterprise. This is creating a rapid shift in IT skills, mindset and investments.
From cloud machine learning to enterprise AI adoption, here are a few areas where businesses are seeing advantages:
Enhancing Products: AI helps improve efficiencies in product design by taking feedback and other data and applying it to usability testing, optimizing features, reducing trial and error with different formats and layouts, and creating a better user experience.
Forecasts and Predictions: Using owned and third-party data, businesses can capitalize on AI models to improve forecasting and prediction capabilities. For instance, a healthcare center can use apps and patient data to identify medical issues earlier and with more accuracy, and a city planner can look at traffic pattern insights to adjust traffic light timing in real time.
Procurement: Working with vendors and contractors can be complicated. AI tools help automate contracts, manage projects and streamline operations.
Customer Service: Enterprises can use call center data to find areas for improving customer service, reducing inefficiency and boosting production. Chatbots and other automated tools help with cybersecurity, regulatory compliance and risk management needs. They also interact with customers in their preferred language, reducing potential miscommunication.
Personalized Experiences: By analyzing customer data, companies can offer experiences designed for individual purchasers, often powered by generative AI. A retailer might offer tailored shopping lists or let users virtually “try” a product before buying it. A hotel or real estate agent can use AI and machine learning to offer digital concierge services and tour buildings, even if the user is in a different location.
McKinsey shared that an AI maturity model is prevalent in most companies — 72% have adopted AI in at least one function, with half of companies using it in at least two functions.
“Going forward, AI and ML solutions are expected to radically transform nearly every industry and field [in the commercial marketplace],” noted Ford.
Enterprise AI Adoption is Scaling Rapidly
Already, 80% of executives believe that automation can be applied to any business decision, and AI and ML tools were the most popular areas where business IT departments invested in 2023. Per a recent Info-Tech Research Group survey, companies today are looking to advance AI through expert models, specialized AI training, simulating human interaction, and countering AI-powered deepfakes, all while maintaining better control of the technology.
Harnessing the business benefits of these technologies requires new strategies for integrating and managing AI and ML solutions across the enterprise, noted Taylor Tresatti, head of industry research for BIZDEV: The International Association for Business Development.
“Not only do we see more and more organizations looking to leverage off-the-shelf, ready-to-go artificial intelligence and machine learning services on an as-needed basis these days, we’re also seeing more businesses looking for ways to quickly tack deep learning capabilities onto preexisting apps, tools and systems in hopes of deriving more value from their existing operations,” Tresatti said. “This can put a growing strain on time-strapped IT departments, who are increasingly on the hunt for solutions that can help them rapidly and cost-efficiently deploy software that allows them to derive more insight from their data.”
Bringing GenAI Into Company Operations
Roughly nine in 10 CEOs report that AI has become a mainstay in their offices, allowing them to increase business productivity, improve decision-making, and enhance customer experiences, according to PwC. More than half of CEOs PwC surveyed (54%) say their companies use Generative AI, which PwC calls the “missing link” for data.
Even more respondents (65%) in McKinsey’s mid-year 2024 report said their companies were using GenAI already, nearly double the rate from 10 months earlier. Three-quarters of respondents believe GenAI will “lead to significant or disruptive change in their industries in the years ahead.”
Google’s The ROI of Gen AI report supports those beliefs, with 74% of companies already seeing ROI within a year of using GenAI. Over eight in 10 companies report revenue increases of at least 6% after implementing GenAI in their businesses.
Businesses are also building their own GenAI apps to enhance company operations and improve customer support. Nutanix created SupportGPT to help System Reliability Engineers (SREs). The app allows SREs to ask hyper-specific questions and receive digestible summaries about Nutanix’s hybrid multicloud software for IT operations. What previously took hours can now be done in only a couple of minutes.
As IT teams are challenged to drive added business performance and efficiency using AI and ML solutions, many embrace automation and new tools to garner actionable business intelligence and effectively manage apps and data. PwC’s 2024 AI Business Survey showed that focusing on one goal before moving to the next wasn’t a recipe for success. Instead, companies that successfully implement AI concentrate on three areas simultaneously: business transformation, enhanced decision-making, and modernized systems and processes.
Business Use of AI Continues to Grow
According to McKinsey’s The State of AI in 2022 — And a Half Decade in Review, adoption more than doubled from 2017 to 2022, though the organizations using AI plateaued between 50 and 60 percent for the past few years. McKinsey found that’s changing this year: Adoption has jumped to 72%.
“Organizations are already seeing material benefits from gen AI use, reporting both cost decreases and revenue jumps in the business units deploying the technology,” the McKinsey report states.
A June 2022 report by Accenture claimed that only 12% of companies using AI are doing so at a maturity level capable of delivering a solid competitive advantage. That means the vast majority are barely scratching the surface of what’s possible. Some use custom-developed internal AI- and ML-powered tools, while others turn to externally-developed solutions.
Heading into 2025, Accenture offered an update: its Reinventing Enterprise Operations with Gen AI report found organizations with fully led, AI-modernized processes nearly doubled in a year, from 9% to 16%. That’s led to stronger performance compared to their peers. As Accenture notes:
These companies experience 2.5 times higher average revenue growth.
They see 2.4 times the improvement in productivity.
They have 3.3 times the success in scaling high-value Gen AI use cases.
Ford predicts that AI-powered capabilities will be an everyday utility that companies of all sizes can tap into as needed, almost like they do for water, heating, cooling, and electricity.
“Deep learning tools will become a resource that can quickly and cost-efficiently be used to solve any challenge,” Ford said. “Going forward, their importance to companies in every sector will grow, as they’re increasingly used to cull through huge mountains of data to arrive at vital insights and actionable strategies.”
IT Teams Prepare Hybrid Multicloud for the AI Era
These technologies are commonly offered by cloud computing service providers, which are racing to create scalable and future-proof AI and ML solutions to meet different industry needs. IT teams will continue to develop custom AI capabilities, but they must work with other AI services across owned and rented data centers. Open-source enterprise software provider Red Hat reports that 78% of enterprise AI and ML ventures are deployed on hybrid cloud infrastructures.
“Certainly, we see companies in every space continuing to experiment with building their own artificial intelligence apps and routines,” said Tresatti. “But at the same time, given the accelerating pace of change and digital transformation, and enterprises’ growing need for agility, the outsourcing of AI and deep learning needs is becoming more common.”
Working with service providers who specialize in these areas makes good sense for many enterprises, Tresatti said.
“Not only does doing so allow firms to get up to speed with and integrate AI and ML offerings into their apps and systems more rapidly, and offload tasks that would otherwise pile on already busy IT departments,” he said. “It also provides companies with the flexibility they need for these tools and solutions to scale, evolve, and change over time.”
The Nutanix State of Enterprise AI Report found most enterprises rely on hybrid or hybrid multicloud IT operations. Most respondents said they deploy AI applications on virtual machines, with 62% saying they deploy AI applications on containers. Additionally, 93% believe in deploying an edge strategy to support AI plans, with 83% willing to increase their edge strategy investments over the next one to three years.
Two years ago, Citi was experiencing compliance issues due to poor-quality data. The bank sought to simplify its technology infrastructure and has retired over 450 applications in 2024 and more than 1,250 since its 2022 investor day.
“The transformation reverses historic underinvestment in Citi’s infrastructure,” Citi CEO Jane Fraser said during the company’s Q3 2024 earnings announcement. “It enhances our risk and control environment and it’s a strategic overhaul, as we’ve talked about, that goes well beyond the consent order to simplify and to strengthen Citi to the benefit of all of the stakeholders we have.”
Citi migrated some of its workloads to private cloud while streamlining public cloud onboarding processes. Per the company, application migration time dropped from nearly two months to two weeks. Citi also saw a 2% reduction in expenses, resulting in hundreds of millions of dollars of savings.
These results showcase how the AI workflow extends across multiple infrastructure environments — and point to a renaissance of sorts with hybrid multicloud.
“AI is probably the best use case for hybrid cloud because there are customers who cannot have their data moved into public cloud,” Sherard Griffin, senior director for Red Hat OpenShift AI, said to CIO Dive, noting GenAI is helping lead a hybrid push. “They now have the choice to train models on-prem and then deploy those models into their cloud provider without sharing sensitive data.”
Evolving AI Business Uses
The growing use of AI is pressuring businesses to hire in-house software and data engineers, AI scientists and ML pros and explore outside services.
Enterprises use AI technologies to assist with process automation, data analysis, customer service enhancement, productivity and personalization. Going forward, experts expect the focus will shift towards forecasting market conditions, enhancing supply chain operations, developing new products, targeting new customer segments, hiring and training employees, and making long-term strategic decisions.
AI will power more self-service tools designed to help professionals gain deeper insights, perform everyday tasks faster and increase worker productivity. These are just some of AI’s big benefits for businesses, according to industry experts, who are discovering more capabilities and possibilities nearly every day.
