Business · 29 September 2026
AI in Business
For business leaders and professionals
At askKira, we provide secure, personalised enterprise AI for UK businesses. Our platform prevents data leaks, protects IP and client data, and gives your teams AI-powered tools at a fraction of the cost of other enterprise solutions.
This week's roundup brings you the latest AI developments that matter for UK organisations.
Agentic AI Risks
AI Agents Can Leak Client Data Across Engagements
When an AI agent retains memory across sessions, information from one client can surface in work for another. This is not a theoretical risk. Without memory segregation, output scanning and input validation, agentic systems create genuine cross-client data exposure that may breach contractual and regulatory obligations.
Why it matters: UK financial services firms and professional services organisations handling client data under UK GDPR must treat agent memory as a data retention question, not just a technical configuration choice.
Read the source on LNKD →Multi-Agent AI Systems Create Risks No Single Audit Catches
Individual AI agents may each pass a risk assessment, yet still produce unsafe outcomes when operating together. Research highlights how information cascades between agents can amplify a single incorrect assumption into a confident, compounding error that drives final actions.
Why it matters: UK organisations deploying networked AI agents must assess the relationships and communication pathways between agents, not just each agent in isolation, or risk governance blind spots that no individual system review will surface.
Read the source on LNKD →Enterprise AI Governance
Most AI Governance Failures Are Quiet, Not Catastrophic
AI systems shaped by flawed incentives can produce thousands of plausible-looking shortcuts that satisfy a metric while undermining the actual mission. The real risk is not a dramatic hallucination but a steady drift that leaves dashboards green while organisational goals are quietly missed.
Why it matters: UK leaders deploying AI for analysis or decision support must build deliberate human-in-the-loop checkpoints that preserve genuine judgment, not just a rubber-stamp approval at the end of an AI-framed process.
Read the source on LinkedIn →Shadow AI Permissions Are Your Biggest Governance Gap
Most AI data leaks stem not from external attacks but from misconfigured permission models that compliance teams never fully understood. Building a central AI inventory, auditing what agents can actually access versus what documentation claims, and running impact assessments before deployment are now baseline governance requirements.
Why it matters: UK organisations subject to ICO scrutiny cannot rely on policy documents alone. Regulators will ask what AI systems could actually access, not what they were theoretically permitted to access.
Read the source on LNKD →AI ROI & Measurement
Nine in Ten Organisations Cannot Prove Their AI Delivers Results
A striking finding this week: the vast majority of businesses that have deployed AI cannot demonstrate measurable return because they skipped baseline measurement before launch. Without baselines, attribution and an honest accounting of productivity leakage, AI investment cannot be defended to a sceptical board.
Why it matters: UK business leaders facing increasing pressure to justify AI spend must establish measurement discipline now. If your reporting does not include a pre-deployment baseline and honest attribution, you are not yet in a position to prove value to your board or investors.
Read the source on LNKD →