“Exploding token efficiency will turn AI from a demo into a digital workforce. When an agent can think for hours for the current cost of a short chat session and not degrade at scale, AI economics shift in favor of autonomous workloads.”
In 2026, the semiconductor industry will shift decisively from raw compute scaling to efficiency-led system design, with tokens per dollar per watt emerging as the dominant metric shaping AI infrastructure investment. Improvements in memory architecture, rack-scale interconnects, heterogeneous silicon, and software-hardware co-design will materially reduce effective memory pressure and idle compute, enabling long-running, stateful agentic workloads to achieve 10-20x gains in tokens per watt. By the end of 2026, memory shortages will no longer be the primary limiter for AI deployment, and energy constraints will increasingly be addressed through a combination of utilization gains, architectural change, and targeted power expansion.
Brendan is Research Director, Semiconductors, Supply Chain, and Emerging Tech. He advises clients on strategic initiatives and leads the Futurum Semiconductors Practice. He is an experienced tech industry analyst who has guided tech leaders in identifying market opportunities spanning edge processors, generative AI applications, and hyperscale data centers.
Before joining Futurum, Brendan consulted with global AI leaders and served as a Senior Analyst in Emerging Technology Research at PitchBook. At PitchBook, he developed market intelligence tools for AI, highlighted by one of the industry’s most comprehensive AI semiconductor market landscapes encompassing both public and private companies. He has advised Fortune 100 tech giants, growth-stage innovators, global investors, and leading market research firms. Before PitchBook, he led research teams in tech investment banking and market research.
Brendan is based in Seattle, Washington. He has a Bachelor of Arts Degree from Amherst College.
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