Observed Signal · Oct 17, 2026 · Opinion / Analysis · Source: CNBC Technology · Impact: 2/5 · Sentiment: Neutral
Paysend CEO Limits AI Access to Top Performers
Paysend CEO Ben Chisell restricts access to general-purpose AI tools to high-performing employees, contrasting with broader AI rollouts at Lloyds Banking Group and Grant Thornton UK. Chisell argues that AI can amplify bad habits and prefers a measured approach. He cites a 25% increase in engineering output with the same team. The article highlights differing strategies: CoreView initially rolled out AI widely but now uses AI agents for coding tasks, while Paysend and Unily favor targeted deployment. UK government research shows 75% of AI-using businesses report productivity gains, but 77% see no revenue change, questioning AI's direct financial impact.
This article provides insights into varying AI adoption strategies in the workplace, which is relevant to MarTech and AdTech as AI tools are increasingly used in marketing and advertising operations. However, it is more of an opinion/analysis piece rather than a specific product launch or corporate announcement.
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Key Takeaways & Evidence Grounding
- Paysend CEO Ben Chisell limits AI tools to top performers.
- Lloyds Banking Group deployed 40,000 Microsoft 365 Copilot licenses.
- Grant Thornton UK invested £500 million in AI, using Anthropic's Claude.
- UK government research: 75% of AI-using businesses report productivity gains, 77% no revenue change.
- Paysend reports 25% more engineering work with same team size.
Connected Companies & Entities
4 Entities mapped“London-based Lloyds Banking Group has rolled out 40,000 Microsoft 365 Copilot licenses...”
“Newcastle-headquartered software company Sage said its AI coding tools had saved hundreds of thousands of work hours...”
“Lloyds Banking Group has rolled out 40,000 Microsoft 365 Copilot licenses...”
“Grant Thornton UK has encouraged all of its staff to use Anthropic's Claude...”
Related Market Signals & Shifts
Recent verified developments and strategic activity across this market segment.
CEOs Are Banning AI Tools in Companies
According to a guest post by entrepreneur Joe Procopio on Inc., an increasing number of company CEOs are issuing partial or complete bans on generative AI tools after experiencing security issues, poor results and fabricated outputs from AI agents. A Section survey cited shows a divergence between leaders (19% report saving >12 hours/week) and employees (40% report no time savings). Examples include firms blocking OpenClaw installations and at least one tech company imposing a total ban on Claude and other AI tools after customer-service errors and an AI agent inventing contacts, which nearly doubled excluded prospects since 2025. The article frames bans as a corrective to hype that could push firms toward more careful, practical AI adoption.
Companies Restrict Employee AI Usage to Curb Token Costs
Many companies are moving from encouraging heavy internal AI use to actively limiting it after discovering how quickly AI 'tokens' can drive large, unpredictable costs with little return. TechCrunch reports that consulting firm Accenture has tried to stop employees from using generative AI for trivial tasks (for example, converting PDFs into slides), following leaked internal audio from Accenture’s agentic AI strategy lead Justice Kwak warning that AI spending is becoming material to cost structures. The story follows broader coverage of “tokenmaxxing” and recent industry cutbacks, amid an AI-related market selloff that has pressured some AI-dependent businesses (notably memory chip makers). The shift reflects growing enterprise scrutiny of AI ROI and internal policy changes to ration usage.
Shadow AI in Companies: Bans Make It Worse
An opinion piece argues that outright bans on employee use of generative AI create uncontrolled 'shadow AI' usage rather than solving data-risk problems. The article cites a US class action alleging Perplexity forwarded millions of chats to Meta and Google (even in incognito), and warns that prompts and follow-up queries can train vendor models, leaking sensitive corporate information. The author describes a successful internal process that vetted and integrated Mistral into an in-house AI platform within 24 hours as an alternative to slow approval cascades. The article recommends structural governance: place decision authority close to subject-matter experts, speed up review/approval processes, and explicitly decide where company data may be processed before rolling out AI tools.
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