Observed Signal · Sep 24, 2026 · Market Signal · Source: BGF · Impact: 3/5
AI ambition is rising. How can growth businesses meet it?
New featured insight article published 24 September 2026: 'AI ambition is rising. How can growth businesses meet it?' Explore the first of our Growth Guides series, which benchmarks SME progress on AI adoption and provides practical guidance to help them move from experimentation to value generation.
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A new path to AI discovery
A research-led look at the state of AI visibility nearly a year on: how to measure it, what shapes AI’s answers and where brands should invest for growth.
AI's Biggest Opportunity: Creating New Value
The article argues that while most organisations use AI (88% per McKinsey), only a small share (6%) see significant enterprise-wide impact because companies mainly apply AI to existing tasks rather than rethinking business models. Only 23% of generative-AI users have redesigned workflows for the technology. The author contrasts a 'factory' (efficiency) mindset with a 'laboratory' (experimentation and effectiveness) mindset and recommends marketing operations lead experimentation to discover new revenue models. Examples include Pieter Levels' portfolio of experiments generating sizable monthly revenue and IKEA’s chatbot 'Billie', which resolved 47% of inquiries, triggered reskilling of call-centre staff into design advisers and produced €1.3 billion in new revenue in 2022. The piece emphasises deliberate, low-cost experimentation to move organisations into higher-value AI stages.
AI Growth Reshapes Enterprise IT and VC Investing
The newsletter argues AI’s adoption is outpacing prior cloud growth, citing striking benchmarks for AWS and Anthropic to illustrate scale. It advises early-stage investors to prioritize founders with deep technical talent, a focused 12–18 month product plan, long-duration missions, and high “learning velocity,” noting compute and engineering hiring as primary constraints and recommending founders identify their top 5–10 early hires. The piece contrasts investment lanes—capital‑intensive physical systems (e.g., robotics) versus the high-throughput AI software “jet stream”—and outlines cybersecurity monetization approaches (pre-empting new attack vectors vs. reimagining existing solutions). It also surveys industry signals: major funding and product moves, regulatory friction, and specific developments from Microsoft, OpenAI, and others.
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