Twice a year I step back and assess where emerging technology is actually heading versus where I expected it to go. This calibration exercise helps update my mental models.

Here’s my current assessment across the major categories I track.

Artificial Intelligence

What I expected: Continued capability improvement, expanding deployment, emerging regulatory frameworks.

What’s happening: Roughly as expected, though with more emphasis on small models and cost efficiency than I anticipated. The “just use GPT-4 for everything” phase has given way to more thoughtful architecture decisions.

Updated view: The next phase is about deployment and integration more than capability advancement. The technology is ahead of organizational ability to use it. AI consultants Sydney report that most client work is implementation rather than cutting-edge capability.

Key uncertainty: How quickly AI agents become reliable enough for truly autonomous operation. Progress is happening but slower than enthusiasts expected.

AI Agents Specifically

What I expected: Rapid expansion of autonomous AI agent deployment across industries.

What’s happening: More cautious than expected. Human-in-the-loop patterns dominate. Fully autonomous agents remain rare except for narrow, well-defined tasks.

Updated view: Trust-building takes longer than capability-building. Agent technology is more capable than organizational willingness to deploy. The gap will close gradually, not suddenly.

Key uncertainty: Whether a killer application emerges that accelerates trust through demonstrated success.

Climate Technology

What I expected: Continued investment, improving economics for renewables and storage, slower progress on harder problems.

What’s happening: Solar and wind economics continue improving beyond expectations. Battery storage is expanding rapidly. Hard-to-decarbonize sectors (steel, cement, aviation, shipping) remain hard.

Updated view: The electricity transition is accelerating. The industrial and transportation transitions remain slow. The gap between what’s economically viable and what’s politically achievable constrains progress.

Key uncertainty: Whether breakthrough battery technology (solid-state or alternatives) reaches scale, which would accelerate multiple transitions simultaneously.

Biotechnology

What I expected: AI acceleration of drug discovery, continued progress in gene therapy, expanding applications of mRNA.

What’s happening: AI-discovered drugs are entering trials but not yet proving superiority. Gene therapy is advancing in specific applications. mRNA is finding uses beyond COVID vaccines.

Updated view: AI in biotech is real but early. The impact will compound over years as the pipeline of AI-influenced drugs progresses through trials.

Key uncertainty: Whether AI-discovered drugs show better success rates in clinical trials, which would validate the approach and accelerate investment.

Quantum Computing

What I expected: Continued technical progress, limited practical application, timeline uncertainty.

What’s happening: Technical progress continues. Error correction is improving. But practical quantum advantage remains elusive for most applications.

Updated view: Quantum is real technology progressing steadily. Practical quantum advantage for commercial applications remains years away. The timeline uncertainty is actually increasing as we understand the challenges better.

Key uncertainty: Whether near-term error correction enables earlier practical applications than currently expected.

Space Technology

What I expected: Continued cost reduction, expanding satellite applications, early space economy formation.

What’s happening: SpaceX dominance continues. LEO satellite constellations are expanding. Commercial space station development is proceeding. Lunar and Mars plans are advancing slowly.

Updated view: The satellite economy is real and growing. Human space activity remains largely government-funded with uncertain commercial viability beyond tourism.

Key uncertainty: Whether SpaceX’s Starship program delivers promised cost reductions and enables new applications.

Autonomous Systems

What I expected: Gradual expansion of autonomous vehicle deployment, growth in robotics applications.

What’s happening: Autonomous vehicles are expanding slowly in specific geographies. Robotics is advancing in controlled environments. General-purpose robotics remains difficult.

Updated view: The timeline for widespread autonomous vehicles keeps extending. Progress is real but slower than predicted. Controlled-environment robotics is more tractable than open-world autonomy.

Key uncertainty: Whether a humanoid robotics breakthrough enables broader applications or whether specialized robotics remains the practical approach.

Implications for Organizations

From these assessments, several implications for organizations:

AI investment is justified but requires patience. The technology works. Deployment takes time. Organizations should invest while managing timeline expectations.

Climate technology creates strategic risk and opportunity. Industries will be disrupted. Being prepared matters.

Don’t wait for quantum. For planning purposes, quantum remains future technology. Current strategies shouldn’t depend on quantum availability.

Autonomous systems will transform specific industries. Logistics, manufacturing, and mining are earlier than personal transportation.

Build optionality. Uncertainty is high across technology categories. Strategies that maintain flexibility outperform those that bet heavily on specific outcomes.

What I’m Watching

The signals that would update my views:

AI agents in production at scale without major incidents. This would accelerate broader adoption.

Grid-scale battery breakthroughs. This would accelerate electricity transition timelines.

AI drug reaching approval with clear AI contribution. This would validate AI in biotech.

Useful quantum computation for commercial problems. This would revise timeline expectations.

Robotaxi service expansion without incidents. This would accelerate autonomous vehicle timelines.

The Meta-Observation

After a decade of tracking emerging technology, one observation dominates: timelines are almost always longer than predicted, while eventual impact is often larger than predicted.

This asymmetry suggests a strategy: maintain exposure to transformative technologies while being patient on timing. Organizations like Team400 help clients navigate this balance - building capability for emerging technology without betting everything on specific timelines.

The future is coming. It’s just not arriving as fast as press releases suggest. Plan accordingly.