AI is moving undercover at work in 2025, according to Deloitte’s Tech Trends report
Every year, Deloitte releases its Tech Trends report, which takes a deep dive into the past year’s technological landscape and identifies macro industry trends that will play a pivotal role in digital transformation in the upcoming 18 to 24 months. Unsurprisingly, artificial intelligence (AI) was a key area in this year’s edition, released today — just not in the same way as in the past.
Even though AI is just as buzzy this year as it was when its popularity exploded two years ago, there have been some significant industry shifts in how technology is perceived, adapted, and deployed by consumers and organizations, which, according to the report, “is being woven into the fabric of our lives.”
Also: OpenAI rolls out Canvas to all ChatGPT users – and it’s a powerful productivity tool
Mike Bechtel, Deloitte’s chief futurist and one of the report’s authors, explained that, much like electricity or the World Wide Web, technologies people rarely think about daily yet rely on for their roles, AI is becoming an underlying layer for key business operations.
“The difference between the next 18 to 24 months and the last 18 to 24 months is that AI is moving undercover,” said Bechtel. “What we’re seeing is that it’s sort of melting into becoming the foundation or sub-structure of all the other business-oriented things that we need to do and think about.”
As AI permeates nearly all business operations, the initial apprehension about the technology is fading. Instead of wondering if they should go all-in on AI, business leaders now face the new hurdle of determining how to exploit the technology, exploring concepts like upgrading hardware, small language models (SLMs), agentic AI, and more.
AI in business: A posse of special-powered agents
When AI chatbots like ChatGPT took the world by storm, the underlying large language models (LLMs) became sought after to optimize business operations. In these case scenarios, a business would have one chatbot that could do it all.
“For the last two years, it felt like AI was a monolithic thing — one chat window for all of our needs and all of our curiosities,” said Bechtel. “What we’re starting to see is this fractal explosion where it’s going to be AIs (plural), dozens and then hundreds and eventually, thousands of domain-specific agents trained on domain-specific data.”
Furthermore, the report explains that, due to the flexible nature of SLMs, each assistant can help organizations carry out a specific task, such as applying for a grant, delivering a financial report, and summarizing an inspection report, all mundane tasks in which training an LLM would be inefficient.
Also: Reddit’s latest AI update makes finding the answers you want much easier
These SLMs will work together, creating a team of virtual assistants that organizations can depend on to complete many tasks. Organizations may approach AI similarly to apps. ‘There’s an app for that’ could well become ‘There’s an agent for that.’
“It’s less of a single super suit; it’s more like a posse, an Avengers team, if you will, of specially powered agents with specialized superpowers that you call on for special needs,” said Bechtel.
Other benefits of SLMs are they can be run on-device, are more cost-efficient, require less data, and are often open-sourced.
AI in hardware
During the past year, there has been an explosion in the amount of AI-centric hardware equipped with more advanced computational power. This hardware can run AI applications on-device and incorporate AI features and workflows.
“An enterprise and employee physical computer refresh is about to start, the likes of which we haven’t seen in 15 years,” said Bechtel. “For the first time in a generation, physical kit, processors, servers, networking, laptops, they can be the key between getting to the future you want, and being stuck in the past.”
Also: Reddit’s latest AI update makes finding the answers you want much easier
This development is forcing companies to consider upgrading their employees’ physical devices, as the AI transformation they envision for their companies is impossible without the proper hardware to support it.
This resurgence in prioritizing hardware investments to meet digital transformation goals led the report to dub one of the six trends: “Hardware is eating the world.”
The most obvious example of this trend is Nvidia’s huge growth in popularity during the past year, with its GPUs becoming one of the hottest commodities, and placing the company as one of the world’s most valuable firms. Deloitte projects the global AI chip market will grow from $50 billion in 2024 to $110bn in 2027 in a conservative forecast or up to $400bn in 2027 in an optimistic forecast.
Ultimately, when deciding when to invest resources into upgrading an organization’s hardware, Bechtel said his go-to advice is to “lead with need.”
“If you have a set of strategic capabilities that you’re champing at the bit to deliver and your hardware estate is your limiting reagent, then, by all means, it’s time,” said Bechtel. “If you’re window shopping sparkly hardware, just because it’s sparkly, that might not be the most value-added decision.”
Where can you get started with AI?
Although the overall AI landscape has significantly changed from 2023, the advice on what area businesses should start with is the same as last year: data.
Ultimately, whether your company is interested in using an LLM or SLM, you will need clean, organized, and up-to-date data to get the right results.
“I think recommendation number one that I give to all my clients in every sector in every geography is clean and normalize and govern your individual data sets before you think of dumping them into an AI,” said Bechtel.
About three-quarters of the clients he speaks to go into meetings thinking they want an AI project, but they walk out realizing they need a data management and governance project.
Also: How Cerebras boosted Meta’s Llama to ‘frontier model’ performance
To avoid “garbage in, garbage squared,” the report suggests data-labeling costs are a big driver of AI investment. Furthermore, Deloitte’s 2024 State of Generative AI in the Enterprise Q3 report found that 75% of surveyed organizations increased their investments in data cycle management because of generative AI.
“When you look at the word ‘IT’ right, you tend to think of the T right, like, ‘oh, technology shiny,’ but the information piece is easily half of the game,” said Bechtel.