Shoppers and industry watchers are poring over Deloitte’s latest Technology, Media & Telecommunications Predictions, and it’s clear why , the report maps how AI is shifting hardware, software, telecom and media, and why that matters for investors, creators, and everyday users in 2026 and beyond.
- Search will feel smarter: AI-crafted summaries will become common, with nearly one-third of adults seeing an AI search summary daily, not just raw links.
- Agentic AI is scaling fast: Enterprise agents could create a $35bn market by 2030, and more thoughtful orchestration might boost that to $45bn.
- Infrastructure demand spikes: Inference workloads will drive chip and data-centre investment, with inference-optimised chips rising over $50bn in 2026.
- Story formats evolve: Microdramas and generative video are booming , short serials and AI video are opening new revenue and trust challenges.
- Practical risk note: Faster innovation brings supply-chain and authenticity risks; moderation, watermarking and regulation will matter.
Why Deloitte’s take feels different this year (and why it smells faintly of the future)
Deloitte isn’t predicting hype so much as hard rewiring , AI is moving from proof-of-concept into lived experience, and you’ll notice it in small ways. Search that used to hand you ten links will increasingly hand you a neat summary, for instance, and that changes how you start every online task. There’s a slightly eerie convenience to it , results feel curated, concise and oddly human.
That shift is already visible across the industry. Analysts from other firms predicted search volumes could fall as chat-style interfaces take over [2], and Deloitte’s numbers give that trend real heft: daily AI search summaries for millions of users by 2026. For businesses and consumers, the immediate payoff is speed and clarity; the trade-offs are transparency and control.
How agentic AI will reshape the apps you use every day
Agentic AI , software agents that act on your behalf , is no longer sci‑fi. Deloitte forecasts companies will pour money into agents across SaaS apps, with up to 75 per cent of firms investing in agentic AI by the end of 2026. That means your CRM, finance tools and project platforms could become more autonomous and proactive, not just smarter interfaces.
Practical result: routine work gets automated, from drafting reports to scheduling meetings, which sounds brilliant until you hit integration snags, governance gaps or unexpected decisions made by agents. The market projections are big: $8.5bn in 2026 growing toward $35bn by 2030, and even higher if enterprises do agent design well. So this is a growth story but one that depends on responsible orchestration.
Expect hardware demand and local control to become political and practical
As agents and generative models proliferate, the compute to run them grows too. Deloitte predicts inference , running trained models , will account for roughly two-thirds of AI compute in 2026, driving demand for inference-focused chips and data-centre upgrades. That’s why chip markets are heating up and why governments are pushing for more local control over supply chains.
You’ll also see more robots and drones in the wild. Industrial robot fleets are set to exceed 5.5 million installed units by 2026, and drone autonomy is improving for inspections and safety use cases. For consumers the change is subtle , smarter devices, faster services and sometimes quieter goods , but for businesses it’s a capital-intensive shift that exposes supply-chain and geopolitical risks.
When entertainment and social collide: short drama, AI video and the trust test
Media is changing in format and tone. Microdramas , short episodic stories made for phones , already reach over half a billion viewers and are forecast to generate much larger in-app revenue by 2026. Meanwhile generative AI is bringing near-Hollywood visuals to smaller creators, which democratizes creativity and raises thorny questions about authenticity.
Platforms now wrestle with a trust problem: realistic AI video can boost engagement, but it can also mislead. Expect increased investment in moderation, watermarking and content labelling, plus likely regulation around age verification and provenance. For viewers, this era means richer content but also a keener need to check what’s behind the polish.
What this means for jobs, skills and everyday users
The tech skills market is already shifting , employers increasingly expect AI literacy and familiarity with automation tools. Role descriptions will evolve as agentic systems take on routine cognitive tasks, so upskilling becomes a practical necessity rather than a buzzword. For everyday users, interfaces will feel more conversational and helpful, and many tasks will become faster and less fiddly.
That said, the report flags real social and economic frictions: supply-chain vulnerabilities, data governance headaches, and the need for laws and platform rules to keep pace. Organisations that prepare for those frictions , governance, transparency and human oversight , will get ahead.
How to act now if you’re a buyer, creator or manager
If you manage tech spend, start by auditing inference costs and thinking long-term about chips and data-centre needs. Creators should experiment with generative video and short serial formats while learning watermarking and consent practices. Consumers will benefit most by checking provenance on realistic content and by choosing services that explain how AI is used.
It’s tempting to chase every shiny AI tool, but Deloitte’s message is clear: the winners will be those who turn AI experimentation into disciplined, responsible adoption.
Ready to test the next wave of AI-powered tools? Check current prices and trial options for agentic platforms and creator tools to see what fits your workflow.