AI Bubbles, Geopatriation and Digital Trust: Communication Priorities for Technology Brands in 2026

If 2024–25 was about AI hype, 2026 is when the bill is due. That was the outtake from two heavyweight forecasters – the Economist Intelligence Unit (EIU) and Gartner. Taken together, their outlooks give communicators a glimpse of what might be in store in 2026: a world where AI matures, geopolitics intrudes on every tech story and digital trust becomes a board-level obsession.

1. From Globalisation to “Geopatriation”: The New Tech Geopolitics

EIU’s tech and telecoms view of 2026 is clear: the sector that benefited most from globalisation is now being re-wired around sovereignty. Governments are subsidising local manufacturing, tightening export controls and pushing for greater control over data, chips and cloud.

Gartner adds a new word to that story: geopatriation – organisations deliberately deciding where critical data and workloads live based on geopolitical risk. Think sovereign clouds, local data centres and on-prem stacks for “crown jewel” systems.

Meanwhile, trust is under attack. As more of us turn to AI for information, incorrect or maliciously seeded answers can spread at scale. EIU calls AI’s political impact and misinformation amongst the most underestimated risks for 2026.

What this means for tech comms:

• Supply chains & local presence become storylines. Where is this built? Where is data stored? How exposed are we geopolitical tensions? Communications teams need simple, confident answers to common questions on where you host, manufacture and hire.
• One-size-fits-all positioning dies. The same global AI or cloud narrative won’t land in every market. PR teams will need regionalised stories that acknowledge regulatory and political realities.
• Deepfake and AI-misinformation scenarios must be in crisis playbooks. Prepare for risks such as fake CEO videos, synthetic news screenshots, spoofed online portals stealing customer data. You are now part of the security conversation – comms must be in the room when discussing cyber incidents and AI misuse.
• Provenance becomes a communications asset. Being able to say “our content and models are watermarked and verifiable” is a differentiator.

2. AI Spending vs AI Reality: The Architect’s Challenge 

Talk of an AI bubble continues, but most EIU data points to increased spending on the technology. But with modest adoption, productivity gains are patchy. Meanwhile, Gartner points to the need to make AI easier to scale, more efficient and trustworthy.

What this means for tech comms:

• Time to stop the magic narrative. AI is no longer a miracle; it’s a tool whose value depends on real use cases, robust infrastructure and strong governance. Messaging should reflect that maturity.
• Internal change comms becomes critical. As AI co-pilots and Agents grow in prominence, people will worry about jobs, skills and relevance. Clear communication about augmentation, not replacement is essential.
• Data privacy is now a brand pillar. Confidential computing and privacy-preserving AI are powerful proof points in a trust story, not just tech architecture.

3. From Single Bots to Multi-Agent Systems: AI Gets Messy (and Useful)

Gartner expects more focus on how AI is actually used in products and workflows. Multi-agent systems (many specialised AI agents that work together), domain-specific language models (DSLMs – smaller LLMs trained on specific domains, like building codes, clinical trials, financial regulation, rather than the entire internet), and physical AI (AI systems embodied in robots, drones and devices that operate in the real world, not just in chat interfaces).

The EIU perspective adds an extra layer: despite enormous hype, AI’s impact on jobs and productivity is uneven and often overstated.

What this means for tech comms:

• Shift from “AI in general” to “AI in context”. The winning stories in 2026 will be about the scope and limits of specific workflows, agents and sector use cases.
• DSLMs are a gift for credibility. Models trained on narrow, regulated domains are easier to explain and trust, an especially strong narrative for highly-regulated brands (healthcare, financial services, public sector).
• Physical AI will need careful public framing. Robots in warehouses, drones near infrastructure, AI in medical devices will spark public concern. Comms will need empathetic, safety-first narratives that highlight human oversight and benefits, not just efficiency.

4. The Chip Squeeze and Quantum Tease: Infrastructure as Narrative

Geopolitical struggles will continue to impact the semiconductor world, while expected AI supercomputing and quantum breakthroughs show that infrastructure is strategic.

What this means for tech comms:

• For B2B tech brands, the “boring” stuff – chips, data centres, power, cooling – is suddenly upfront.
• There’s a storytelling opportunity around:
  - Resilient, diversified supply chains
  - Sustainable compute and energy use
  - Preparing for the “next wave” (quantum) without overhyping it

The companies that can explain it clearly will win mindshare with media, policymakers and investors.

A 2026 To-Do List for Tech Comms Leaders

Bringing the EIU and Gartner perspectives together, here’s what communications teams should be doing now:

1. Audit your AI story.

• Does it overpromise?
• Is it grounded in actual adoption and ROI?
• Does it explain benefits and limits?

2. Build a sovereignty and geopolitics narrative.

• Where is your brand exposed?
• How are you managing data residency, supply chains and sovereign cloud?
• Can you tell that story simply to non-technical stakeholders?

3. Refresh crisis playbooks for the AI era.

• Include deepfakes, AI-driven phishing, model failures and third-party SaaS compromises.
• Pre-draft holding statements and Q&A for these scenarios.

4. Partner up with IT, security and legal.

• You can’t credibly talk about digital trust without them.
• Get regular briefings on AI security, provenance and infrastructure choices.

5. Shape people-first AI narratives.

• Highlight augmentation over replacement.
• Showcase training, reskilling and the use of domain-specific models and agents to make work safer and smarter.