Tech Trends 2025: AI Everywhere
Tech Trends 2025: AI Everywhere
Tech Trends 2025: AI Everywhere
@TrendSpotting2 weeks ago
Tech Trends 2025
In Deloitte's 16th annual Tech Trends report, AI is the common thread of nearly every trend. Moving forward, it will be part of the substructure of everything we do.
rends 2025
ech T
T
i
- 37 . . . IT, amplified: AI elevates the reach (and remit) of the tech function
- 45 . . . The new math: Solving cryptography in an age of quantum
- 53 . . . The intelligent core: AI changes everything for core modernization
- 60 . . . Breadth is the new depth: The power of intentional intersections
- · Spatial computing takes center stage: Future AI advancements will enhance spatial-computing simulations, eventually leading to seamless spatial-computing experiences integrated with AI agents.
- · What's next for AI?: As AI evolves, the enterprise focus on large language models is giving way to small language models, multimodal models, AI-based simulations, and agents that can execute discrete tasks.
- · Hardware is eating the world: After years of software dominance, hardware is reclaiming the spotlight, largely due to AI's impact on computing chips and its integration into end-user devices, the Internet of Things, and robotics.
- · IT, amplified: AI elevates the reach (and remit) of tech talent: AI's applicability to writing code, testing software, and augmenting tech talent is transforming IT and sparking a shift away from virtualization and austere budgets.
- · The intelligent core: AI changes everything for core modernization: Core systems providers have invested heavily in AI, which may simplify the user experience and data-sharing across applications but will make these systems more complex at an architectural level.
02 . . . Executive summary
INTRODUCTION
05 . . . AI everywhere: Like magic, but with algorithms
INTERACTION
09 . . . Spatial computing takes center stage
INFORMATION
17 . . . What's next for AI?
COMPUTATION
27 . . . Hardware is eating the world
BUSINESS OF TECHNOLOGY
CYBER AND TRUST
CORE MODERNIZATION
CONCLUSION
Executive summary
Tech Trends, Deloitte's flagship technology report, explores the emergence of trends in three elevating forces (interaction, information, and computation) and three grounding forces (business of technology, cyber and trust, and core modernization)-all part of our macro technology forces framework (figure 1). Tech Trends 2025, our 16th trip around the sun, previews a future in which artificial intelligence will be as foundational
as electricity to daily business and personal lives. As our team in Deloitte's O/ffice of the CTO put finishing touches on Tech Trends 2025, we realized that AI is a common thread in nearly every trend. We expect that going forward, AI will be so ubiquitous that it will be a part of the unseen substructure of everything we do, and we eventually won't even know it's there.
Introduction
AI everywhere: Like magic, but with algorithms
Generative AI continues to be the buzzword of the year, but Tech Trends 2025-and in fact, the future of technology-is about much more than AI. This year's report reveals the extent to which AI is being woven into the fabric of our lives. We'll eventually take it for granted and think of it in the same way that we think of HTTP or electricity: We'll just expect it to work. AI will perform quietly in the background, optimizing tra/ffic in our cities, personalizing our health care, or creating adaptative and accessible learning paths in education. We won't proactively use it; we'll simply experience a world in which it makes everything work smarter, faster, and more intuitively-like magic, but grounded in algorithms. The six chapters of Tech Trends 2025 reflect this emerging reality.
Interaction
Spatial computing takes center stage
Spatial computing continues to spark enterprise interest because of its ability to break down information silos and create more natural ways for workers and customers to interact with information. We're already seeing enterprises find success with use cases like advanced simulations that allow organizations to test di/fferent scenarios to see how various conditions will impact their operations. With a stronger focus on e/ffectively managing spatial data, organizations can drive more cutting-edge applications. In the coming years, advancements in AI could lead to seamless spatial computing experiences and improved interoperability, ultimately enabling AI agents to anticipate and proactively meet users' needs.
Information
What's next for AI?
To take advantage of the burgeoning excitement around generative AI, many organizations have already adopted large language models (LLMs), the best option for many use cases. But some are already looking ahead. Despite their general applicability, LLMs may not be the most
e/fficient choice for all organizational needs. Enterprises are now considering small language models and opensource options for the ability to train LLMs on smaller, more accurate data sets. Together with multimodal models and AI-based simulations, these new types of AI are building a future where enterprises can find the right type of AI for each task. That includes AI that not only answers questions but also completes tasks. In the coming years, a focus on execution may usher in a new era of agentic AI, arming consumers and organizations with co-pilots capable of transforming how we work and live.
Computation
Hardware is eating the world
After years of software dominance, hardware is reclaiming the spotlight. As AI demands specialized computing resources, companies are turning to advanced chips to power AI workloads. In addition, personal computers embedded with AI chips are poised to supercharge knowledge workers by providing access to o/ffline AI models while 'future-proofing' technology infrastructure, reducing cloud computing costs, and enhancing data privacy. Although AI's increased energy demands pose sustainability challenges, advancements in energy sources and e/fficiency are making AI hardware more accessible. Looking forward, AI's continued integration into devices could revolutionize the Internet of Things and robotics, transforming industries like health care through smarter, more autonomous devices.
Business of technology
IT, amplified: AI elevates the reach (and remit) of tech talent
After years of progressing toward lean IT and everything-as-a-service o/fferings, AI is sparking a shift away from virtualization and austere budgets. Long viewed as the lighthouse of digital transformation throughout the enterprise, the IT function is now taking on AI transformation. Because of generative AI's applicability to writing code, testing software, and augmenting tech talent in general, forward-thinking technology leaders are using the current moment as a once-in-a-blue-moon
opportunity to transform IT across five pillars: infrastructure, engineering, finance operations, talent, and innovation. As both traditional and generative AI capabilities grow, every phase of tech delivery could see a shift from human in charge to human in the loop. Such a move could eventually return IT to a new form of lean IT, leveraging citizen developers and AI-driven automation.
Cyber and trust
The new math: Solving cryptography in an age of quantum
In their response to Y2K, organizations saw a looming risk and addressed it promptly. Today, IT faces a new challenge, and it will have to respond in a similarly proactive manner. Experts predict that quantum computers, which could mature within five to 20 years, will have significant implications for cybersecurity because of their ability to break existing encryption methods and digital signatures. This poses a risk to the integrity and authenticity of data and communications. Despite the uncertainty of the quantum computer timeline, inaction on post-quantum encryption is not an option. Emerging encryption standards o/ffer a path to mitigation. Updating encryption practices is fairly straightforward-but it's a lengthy process, so organizations should act now to stay ahead of potential threats. And while they're at it, they can consider tackling broader issues surrounding cyber hygiene and cryptographic agility.
Core modernization
The intelligent core: AI changes everything for core modernization
Core systems providers have invested heavily in AI, rebuilding their o/fferings and capabilities around an AI-fueled or AI-first model. The integration of AI into
core enterprise systems represents a significant shift in how organizations operate and leverage technology for competitive advantage. This transformation is about automating routine tasks and fundamentally rethinking and redesigning processes to be more intelligent, e/fficient, and predictive. It requires careful planning due to integration complexity, strategic investment in technology and skills, and a robust governance framework to ensure smooth operations. But beware of the automation paradox: The more complexity is added to a system, the more vital human workers become. Adding AI to core systems may simplify the user experience, but it will make them more complex at an architectural level. Deep technical skills are still critical for managing AI in core systems.
Conclusion
Breadth is the new depth: The power of intentional intersections
Organizations have long relied on innovation-driven new revenue streams, synergies created through mergers and acquisitions, and strategic partnerships. But increasingly, segmentation and specialization have given way to intentional intersections of technologies and industries. For example, when two technologies intersect, they are often complementary, but they can also augment each other so that both technologies ultimately accelerate their growth potential. Similarly, new opportunities can emerge when companies aim to extend their market share by purposefully partnering across seemingly disparate industries.
AI everywhere: Like magic, but with algorithms
Tech Trends 2025 reveals how much artificial intelligence is being woven into the fabric of our lives-making everything work smarter, faster, and more intuitively Kelly Raskovich
Two years after generative artificial intelligence staked its claim as the free space on everyone's buzzword-bingo cards, you'd be forgiven for imagining that the future of technology is simply ⦠more AI. That's only part of the story, though. We propose that the future of technology isn't so much about more AI as it is about ubiquitous AI. We expect that, going forward, AI will become so fundamentally woven into the fabric of our lives that it's everywhere, and so foundational that we stop noticing it.
Take electricity, for example. When was the last time you actually thought about electrons? We no longer marvel that the lights turn on-we simply expect them to work. The same goes for HTTP, the unseen thread that holds the internet together. We use it every day, but I'd bet most of us haven't thought about (let alone uttered) the word 'hypertext' in quite some time.
AI will eventually follow a similar path, becoming so ubiquitous that it will be a part of the unseen substructure of everything we do, and we eventually won't even know it's there. It will quietly hum along in the background, optimizing tra/ffic in our cities, personalizing our health care, and creating adaptative and accessible learning paths in education. We won't 'use' AI. We'll just experience a world where things work smarter, faster, and more intuitively-like magic, but grounded in algorithms. We expect that it will provide a foundation for business and personal growth while also adapting and sustaining itself over time.
Nowhere is this AI-infused future more evident than in this year's Tech Trends report, which each year explores emerging trends across the six macro forces of information technology (figure 1 in the executive summary). Half of the trends that we've chronicled are elevating forces-interaction, information, and computation-that underpin innovation and growth. The other half-the grounding forces of the business of technology, cyber and trust, and core modernization-help enterprises seamlessly operate while they grow.
As our team put the finishing touches on this year's report, we realized that this sublimation and di/ffusion of AI is already afoot. Not the 'only trend' nor 'every trend,' AI is the sca/ffolding and common thread buttressing nearly every trend. (For those keeping a close eye at home, 'The new math: Solving cryptography in an age of quantum'-about the cybersecurity implications of another game-changing technology, quantum computing-is the only one in which AI does not have a foundational role. Yet behind the scenes, AI advancements are accelerating advances in quantum.)
Because we expect AI to become part of tomorrow's foundational core-like electricity, HTTP, and so many other technologies-it's exciting to think about how AI might evolve in the next few years as it marches toward ubiquity, and how we as humans may benefit. We here at Tech Trends will be chronicling every step of the journey.
Until next time,
Kelly Raskovich O/ffice of the CTO Executive editor, Tech Trends
Note: To learn more about past Tech Trends, go to www.deloi/t_te.com/us/TechTrends Source: Deloi/t_te analysis.
8
Spatial computing takes center stage
What is the future of spatial computing? With real-time simulations as just the start, new, exciting use cases can reshape industries ranging from health care to entertainment.
Kelly Raskovich, Bill Briggs, Mike Bechtel, and Ed Burns
Today's ways of working demand deep expertise in narrow skill sets. Being informed about projects often requires significant specialized training and understanding of context, which can burden workers and keep information siloed. This has historically been true especially for any workflow involving a physical component. Specialized tasks demanded narrow training in a variety of unique systems, which made it hard to work across disciplines.
One example is computer-aided design (CAD) software. An experienced designer or engineer can view a CAD file and glean much information about the project. But those outside of the design and engineering realm-whether they're in marketing, finance, supply chain, project management, or any other role that needs to be up to speed on the details of the work-will likely struggle to understand the file, which keeps essential technical details buried.
Spatial computing is one approach that can aid this type of collaboration. As discussed in Tech Trends 2024 , spatial computing o/ffers new ways to contextualize business data, engage customers and workers, and interact with digital systems. It more seamlessly blends the physical and digital, creating an immersive technology ecosystem for humans to more naturally interact with the world. 1 For example, a visual interaction layer that pulls together contextual data from business software can allow supply chain workers to identify parts that need to be ordered and enable marketers to grasp a product's overall aesthetics to help them build campaigns. Employees across the organization can make meaning of and, in turn, make decisions with detailed information about a project in ways anyone can understand.
If eye-catching virtual reality (VR) headsets are the first thing that come to mind when you think about spatial computing, you're not alone. But spatial computing is about more than providing a visual experience via a pair of goggles. It also involves blending standard business sensor data with the Internet of Things, drone, light detection and ranging (LIDAR), image, video, and other three-dimensional data types to create digital representations of business operations that mirror the real world. These models can be rendered across a range of interaction media, whether a traditional two-dimensional screen, lightweight augmented reality glasses, or full-on immersive VR environments.
Spatial computing senses real-world, physical components; uses bridging technology to connect physical and digital inputs; and overlays digital outputs onto a blended interface (figure 1). 2
Spatial computing's current applications are as diverse as they are transformative. Real-time simulations have emerged as the technology's primary use case. Looking ahead, advancements will continue to drive new and exciting use cases, reshaping industries such as health care, manufacturing, logistics, and entertainmentwhich is why the market is projected to grow at a rate of 18.2% between 2022 and 2033. 3 The journey from the present to the future of human-computer interaction promises to fundamentally alter how we perceive and interact with the digital and physical worlds.
Figure 1
The possibilities of spatial operations
Physical
Wearables (for example, headset, smart eyewear, and pins)
Next-gen displays
Internet of Things devices (for example, biometric devices)
Sensory tech (for example, haptic suits)
Spatial audio devices
Cameras
Digital
Augmented reality objects
Interactive digital objects
Holographic projections
Audio outputs
Avatars
Generative AI
Bridging
Sensors (for example, LIDAR) and sensor fusion
Computer vision
GPS/spatial mapping so/f_tware
3D design and rendering tools
Comprehensive next-gen network infrastructure
Data lakes
Next-gen ba/t_teries
Source: Abhijith Ravinutala et al., 'Dichotomies spatial computing: Navigating towards a be/t_ter future,' Deloi/t_te, April 22, 2024.
Now: Filled to the rim with sims
At its heart, spatial computing brings the digital world closer to lived reality. Many business processes have a physical component, particularly in asset-heavy industries, but, too often, information about those processes is abstracted, and the essence (and insight) is lost. Businesses can learn much about their operations from well-organized, structured business data, but adding physical data can help them understand those operations more deeply. That's where spatial computing comes in.
'This idea of being served the right information at the right time with the right view is the promise of spatial computing,' says David Randle, global head of go-to-market for spatial computing at Amazon Web Services (AWS). 'We believe spatial computing enables more natural understanding and awareness of physical and virtual worlds.' 4
One of the primary applications unlocked by spatial computing is advanced simulations. Think digital twins, but rather than virtual representations that monitor physical assets, these simulations allow organizations to test di/fferent scenarios to see how various conditions will impact their operations.
Imagine a manufacturing company where designers, engineers, and supply chain teams can seamlessly work from a single 3D model to craft, build, and procure all the parts they need; doctors who can view true-to-life simulations of their patients' bodies through augmented reality displays; or an oil and gas company that can layer detailed engineering models on top of 2D maps. The possibilities are as vast as our physical world is varied.
The Portuguese soccer club Benfica's sports data science team uses cameras and computer vision to track players
throughout matches and develop full-scale 3D models of every move its players make. The cameras collect 2,000 data points from each player, and AI helps identify specific players, the direction they were facing, and critical factors that fed into their decision-making. The data essentially creates a digital twin of each player, allowing the team to run simulations of how plays would have worked if a player was in a di/fferent position. X's and O's on a chalkboard are now three-dimensional models that coaches can experiment with. 5
'There's been a huge evolution in AI pushing these models forward, and now we can use them in decision-making,' says Joao Copeto, chief information and technology o/fficer at Sport Lisboa e Benfica. 6
This isn't only about wins and losses-it's also about dollars and cents. Benfica has turned player development into a profitable business by leveraging data and AI. Over the past 10 years, the team has generated some of the highest player-transfer deals in Europe. Similar approaches could also pay dividends in warehouse operations, supply chain and logistics, or any other resource planning process.
Advanced simulations are also showing up in medical settings. For instance, virtual patient scenarios can be simulated as a training supplement for nurses or doctors in a more dynamic, self-paced environment than textbooks would allow. This may come with several challenges, such as patient data concerns, integration of AI into existing learning materials, and the question of realism. But AI-based simulations are poised to impact the way we learn. 7
Simulations are also starting to impact health care delivery. Fraser Health Authority in Canada has been a pioneer in leveraging simulation models to improve care. 8 By creating a first-of-its-kind system-wide digital twin, the public health authority in British Columbia generated powerful visualizations of patient movement through di/fferent care settings and simulations to determine the impact of deploying di/fferent care models on patient access. Although the work is ongoing, Fraser expects improvement in appropriate, need-based access to care through increased patient awareness of available services.
New: Data is the di/fferentiator
Enterprise IT teams will likely need to overcome significant hurdles to develop altogether-new spatial computing applications. They likely haven't faced these hurdles when implementing more conventional software-based projects. While these projects have compelling business value, organizations will have to navigate some uncharted waters to achieve them.
For one thing, data isn't always interoperable between systems, which limits the ability to blend data from di/fferent sources. Furthermore, the spaghetti diagrams mapping out the path that data travels in most organizations are circuitous at best, and building the data pipelines to get the correct spatial data into visual systems is a thorny engineering challenge. Ensuring that data is of high quality and faithfully mirrors real-world conditions may be one of the most significant barriers to using spatial computing e/ffectively. 9
Randle of AWS says spatial data has not historically been well managed at most organizations, even though it represents some of a business's most valuable information.
'This information, because it's quite new and diverse, has few standards around it and much of it sits in silos, some of it's in the cloud, most of it's not,' says Randle. 'This data landscape encompassing physical and digital assets is extremely scattered and not well managed. Our customers' first problem is managing their spatial data.' 10
Taking a more systematic approach to ingesting, organizing, and storing this data, in turn, makes it more available to modern AI tools, and that's where the real learnings begin.
Data pipelines deliver the fuel that drives business
We've often heard that data is the new oil, but for an American oil and gas company, the metaphor is becoming reality thanks to significant e/ffort in replumbing some of its data pipelines.
The energy company uses drones to conduct 3D scans of equipment in the field and its facilities, and then applies