Business · 17 March 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.
AI Ethics and Trust
Grammarly Faces Severe Industry Backlash Over Controversial AI Feature Launch
On 8 March, Grammarly launched an 'AI expert review' feature that reportedly used the identities of real academics without their consent. The incident has sparked significant industry backlash regarding data privacy and the ethical deployment of artificial intelligence.
Why it matters: UK organisations must ensure any AI tools they deploy strictly adhere to UK GDPR consent requirements to avoid severe ICO penalties and reputational damage.
Read the source on LinkedIn →Workforce Productivity
Generative AI Closes Workplace Productivity Gaps But Masks Underlying Skill Deficits
A new study involving over a thousand professionals reveals that generative AI access shrinks the productivity gap between high and low-education workers by 75 percent. However, once the AI assistance is removed, the original skill disparities immediately reappear.
Why it matters: UK business leaders must balance AI deployment with structured training programmes to ensure staff build genuine capabilities rather than just masking skill gaps.
Read the source on LinkedIn →Theoretical AI Capability Continues To Outpace Real World Business Adoption Rates
Recent data analysed by Anthropic indicates that while AI can theoretically automate up to 70 percent of routine tasks in sectors like software development, actual adoption remains significantly lower. Most companies are currently choosing to use AI for staff augmentation rather than role replacement.
Why it matters: UK firms have a unique window to safely integrate AI as an augmentation tool before competitors fully optimise their operational models for automation.
Read the source on LinkedIn →Enterprise Risk and Governance
Corporate Leaders Increasingly Prioritise Implementation Speed Over Proper AI Governance Controls
A 9 March report from CIO Dive highlights a growing trend of 'Shadow AI' where businesses allow staff to use artificial intelligence without formal compliance frameworks. Executives are increasingly accepting higher operational risks to achieve faster implementation speeds.
Why it matters: UK boards taking a blind eye to unapproved AI tools risk severe regulatory action from bodies like the FCA and ICO if client data is compromised.
Read the source on LinkedIn →Global Data Report Highlights Significant AI Literacy Gaps Across The Corporate Workforce
A fresh DataCamp and YouGov report reveals that while corporate AI investment is surging, workforce readiness remains low. The findings contrast the structured US approach to AI literacy with the UK model which embeds capability within broader digital and responsible AI initiatives.
Why it matters: UK organisations cannot rely solely on national digital skills programmes and must urgently develop internal AI literacy frameworks to remain globally competitive.
Read the source on LinkedIn →Data Security and Operations
Unsecured Employee AI Access Creates Major Intellectual Property And Data Vulnerabilities
Security experts warn that employees accessing public AI models via standard web browsers pose a massive data leak risk. Pasting sensitive contracts or financial documents into third-party platforms effectively moves company data outside the established security perimeter.
Why it matters: UK businesses must implement secure enterprise environments or dedicated AI gateways to protect intellectual property and maintain strict UK GDPR compliance.
Read the source on LinkedIn →Anthropic Research Warns Long Cycle AI Tasks Can Lead To Industrial Accidents
New research from Anthropic demonstrates that AI models often fail unpredictably during long-cycle reasoning tasks. These breakdowns compound into incoherence over time, leading researchers to compare the failures to industrial accidents rather than simple algorithmic bias.
Why it matters: UK operations and manufacturing leaders must break AI workflows into smaller verifiable steps with human validation to prevent catastrophic process failures.
Read the source on LinkedIn →