Predictions are hazardous. Technology forecasting is especially prone to both excessive optimism and failure to anticipate genuine disruption. With appropriate humility, here’s my assessment of what 2026 likely holds.

I’ve been making technology predictions for years, tracking my accuracy. This shapes my confidence levels.

High Confidence Predictions

Things likely to happen:

AI agents become mainstream enterprise tools: Not replacing workers, but augmenting them meaningfully. Customer service, coding, analysis, and content operations see widespread agent adoption.

Edge AI deployment accelerates: More processing moves to devices. Privacy, latency, and cost drive the shift. On-device AI becomes expected capability.

Cybersecurity gets harder: AI-powered attacks increase in sophistication. Organizations struggle to keep pace. Major breaches continue.

Cloud costs get scrutinized: After years of uncritical cloud migration, organizations examine actual costs versus benefits. Some workloads move back on-premise or to hybrid models.

Battery costs continue declining: Energy storage becomes more economically attractive. Electric vehicle adoption continues in markets with supporting infrastructure.

Medium Confidence Predictions

Likely but less certain:

Multimodal AI becomes standard: AI systems that see, hear, and read become the norm rather than novelty. Applications requiring multiple modalities proliferate.

AI regulation takes effect: EU AI Act implementation begins affecting global AI development. Other jurisdictions follow with their own frameworks.

Autonomous trucking reaches commercial operation: Limited routes, specific conditions, but real commercial deployments generating revenue.

Brain-computer interfaces expand clinical trials: More patients receive implants. Data accumulates on efficacy and safety.

Quantum computing remains pre-commercial: Continued progress but still not solving business problems better than classical computers for most applications.

Lower Confidence Predictions

Possible but uncertain:

Major AI capability breakthrough: The pace of fundamental AI progress is unpredictable. A significant capability jump could happen—or progress could plateau.

Tech regulation intensifies globally: Political and public pressure exists. Whether it translates to meaningful action is unclear.

Hardware constraints ease: NVIDIA alternatives gain share. Supply improves. Or constraints persist and shape what’s possible.

Climate tech breakout: Some climate technology reaches inflection point of cost and scale. Which one and when is uncertain.

What I’m Watching

Signals that would change my predictions:

AI reasoning capabilities: Can AI systems solve genuinely novel problems? Progress here changes everything.

Energy costs: Energy prices affect everything from AI compute economics to manufacturing competitiveness.

Geopolitical developments: Technology increasingly shaped by geopolitics. US-China relations, trade policy, and conflict all matter.

Labor market dynamics: How AI affects employment determines political response and adoption patterns.

Sectors to Watch

Industries with significant technology impact in 2026:

Healthcare: AI diagnostics, drug discovery acceleration, digital health integration.

Financial services: AI in trading, risk, fraud detection, and customer service.

Manufacturing: Robotics acceleration, AI-powered quality and optimization.

Energy: Storage deployment, grid modernization, clean energy scaling.

Transportation: Electric vehicle adoption, autonomous vehicle progress, logistics automation.

What Won’t Happen

Equally important—things unlikely despite hype:

Artificial general intelligence: Not in 2026. Progress continues but AGI remains years away at minimum.

Mass AI job displacement: AI will change jobs more than eliminate them in the near term. The transition is gradual.

Quantum computing going mainstream: Still in experimental and early commercial phase. Practical business applications limited.

Autonomous vehicle ubiquity: Expansion continues but robotaxis remain in limited cities. Personal autonomous vehicles years away.

Metaverse adoption: VR/AR remains niche. Killer applications still missing.

For Business Leaders

What this means for strategy:

AI is essential: Organizations without AI strategies will fall behind. The question is where and how to deploy.

Security requires attention: AI introduces new risks. Security investment must match AI investment.

Talent remains critical: Technical talent, especially AI and security expertise, continues commanding premium.

Flexibility matters: Technology changes fast. Strategies that allow adaptation outperform rigid plans.

Fundamentals still apply: Technology doesn’t change basic business principles. Customer value, operational efficiency, and sound economics still win.

My Track Record

Accountability for past predictions:

2024 predictions accuracy: Approximately 70% of high-confidence predictions proved correct. Medium-confidence closer to 50%.

Biggest miss: Underestimated the pace of AI model improvement. Capabilities advanced faster than expected.

Biggest hit: Predicted enterprise AI adoption would lag model capability. Organizations still struggle to deploy effectively.

I expect similar accuracy in 2026—mostly right on likely trends, occasionally surprised by timing.

The Uncertainty Principle

Technology prediction is inherently uncertain:

Black swans exist: Unexpected events change trajectories.

Compounding effects: Small changes early have large effects later.

Human behavior matters: Technology adoption depends on people, not just capability.

Prediction affects reality: Public predictions change what people do.

The value isn’t in being right but in thinking systematically about what might happen and preparing accordingly.

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Annual technology forecast with appropriate uncertainty acknowledgment.