Deloitte’s 16th Annual ‘Tech Trends’ Report Reveals AI is Quickly Becoming Foundational to the Modern Enterprise

The report details six AI-fueled trends shaping business operations, growth and transformation

Key takeaways

• AI is everywhere. From the server room to the board room, it’s becoming foundational to enterprise IT, and an indispensable ingredient in the design and delivery of new products and services. That said, organizations face an imperative to fully align strategy, talent, architecture and most importantly, data, before they can realize AI’s full potential.
• Today & Tomorrow Inc. Leaders are adopting a “Best of Both Worlds” philosophy. An integrative approach that balances investments in both foundational and emerging technologies is proving essential to unlocking growth and realizing the totality of tech impact.
• Convergence dominates. Siloed, standalone technologies are giving way to interconnected business solutions as they adapt to the needs of different industries. And while AI leads today’s conversations, huge potential lies in unlocking adjacent tech like spatial interfaces, next-gen chipsets, quantum and more if the challenges of scaling, data hygiene and energy consumption can be overcome.

Also Read: BasedAI Mainnet Launch Unleashes Decentralized AI for a Secure, Private Future

Why this matters
Today’s AI technology is being embedded everywhere to create the tech capabilities businesses will rely on for decades to come. As such, solid fundamentals are critical. A barrier to entry? Modern architecture capable of supporting the tomorrow’s processes, talent, and systems at scale.

Deloitte’s 16th annual “Tech Trends” report — built on deep cross-industry experience and real-world stories — shines a light on the following trends poised to graduate from sensational to foundational over the next 18-24 months.

Interaction: Spatial interaction for a world in three dimensions
Taking the visualization of ideas and objects off the 2D screen and adding voice and gesture to the ways people interact with machines is not just a growing technical capability — it’s a surging interest. The use of spatial computing is evolving, fueled by its ability to contextualize data and engage people. Scaling this technology to meet modern demands and use cases will require new hardware, software, skillsets and mindsets. Thanks to AI, spatial computing is maturing from a useful training tool that benefits a specific set of workers to an enterprise profit center that can deliver real-time, advanced data analysis and automatic adjustments.

Information: Smaller models help AI get even bigger
Turning to hyperscalers for LLMs instead of building from scratch has helped many enterprises accelerate their AI adoption. But size isn’t everything — and sometimes it stands in the way of specialization and flexibility. Some organizations are turning to smaller, purpose-built models because of security, energy use, agent-to-agent communication, and other specific needs. Multiple small models can work in concert to address discrete tasks, generate multimodal outputs, run simulations, and arm users with multiple virtual assistants. Thanks to small and open-source models, yesterday’s “there’s an app for that” may become tomorrow’s “there’s an agent for that.”

Computation: In PCs and the IoT, AI gets physical
Remember hardware? AI isn’t just software anymore. Manufacturers are pioneering a new generation of chips that embed AI models into PCs and edge devices for localized, offline use, not only supercharging user capabilities but future-proofing the tech infrastructure. Onboard AI can also make the Internet of Things (IoT) more robust in areas like medical devices and robotics. It isn’t only the processors’ power that’s improving; they’re becoming more energy efficient as well, a major consideration given the growing energy appetite of global computing. Companies that moved away from hardware at the core may end up making fresh investments in hardware at the edge, but not without a strong vision and business case.

The business of IT: Technician, heal thyself
New AI-based capabilities for writing code, testing software and augmenting human talent are beginning to transform the technology teams and functions within organizations. This may signal a shift away from the “thin IT” path and its reliance on “as-a-service” offerings as new capabilities come to reside inside the enterprise, and software engineering continues to evolve as a cross-industry strategic fulcrum. But a new kind of thin IT may emerge after that, as AI democratizes development, and IT orchestrates large portions of today’s manual workload. It’s possible AI may eventually recast IT into an “outcome-a-S” in its own right, delivered to the enterprise by a combination of carbon and silicon.

Also Read: AiThority Interview with Balakrishna D.R. (Bali) – Global Head for AI and Automation, Infosys

Cyber: Today’s protections face an expiration date
Quantum computing’s march toward maturity represents an opportunity — and a deadline. Its unprecedented decryption power could make current cybersecurity practices a greater liability than two-digit year codes were at the end of 1999. As with Y2K, work on the solution has to start in advance. Where Y2Q is different? The looming deadline doesn’t have a hard and fixed date to work against. NIST is making inroads on new encryption standards, and it will be up to every organization to reimagine its cyber mindset. What’s at stake? Identities, finances, communications — anything you entrust to computers today, or might tomorrow.

Core modernization: The complexity of simplicity
Integrating AI into core enterprise architecture drives deep change in systems and processes. The aim is to give users a more streamlined experience, but it takes complex orchestrated architectures to make that simplicity possible. Meanwhile, enterprises continue to rely on (and invest in) legacy custom systems, ERP and customized cloud solutions. AI can and will be embedded into those systems but might also lead to a recast of the “core” content, data, and transactions — especially as AI trains on data from across the organization and potentially beyond.

Key quotes

“Leaders from the boardroom on down are feeling pressure to innovate with technology and invest in modernizing their core tech, while managing flat budgets. This creates significant tension. One way to alleviate this is by building institutional resistance to the allure of ‘shiny object syndrome.’ Our research puts those advances in context with what it will take to make it real at scale. The future of technology is more knowable than it might feel — but it ultimately doesn’t matter unless you can translate tech potential to operational, market or mission advantage.”

— Bill Briggs, chief technology officer, Deloitte Consulting LLP and Deloitte LLP

“Technology has been a force multiplier in every era, but especially in the coming era of AI everywhere, we will see human empowerment. As AI is being embedded in the core, suddenly there’s permission to scale-up, not just start-up, freeing leaders from the frenzy of discovery and letting them focus on deployment. Businesses and people will benefit as technologies converge to unlock new ways of working.”

— Mike Bechtel, chief futurist, Deloitte Consulting LLP

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