From the Citizen Engagement & Services edition of November 9, 2026
South Kesteven District Council answered 73.24% of 268 FOI requests on time in Q2 against a 95% target; officers blame longer, more complex requests and councillors' AI-generated FOIs
South Kesteven District Council (Governance and Audit Committee) · Local government public records (FOI) requests · South Kesteven, Lincolnshire, England, United Kingdom
- Publisher
- LincsOnline (Local Democracy Reporting Service)
- Original publication
- 2026-11-06
- Source retrieved
- 2026-11-10
- Event date
- 2026-11-05
What happened
At its Nov. 5, 2026 governance and audit committee meeting, South Kesteven District Council reported receiving 268 FOI requests in Q2 of the financial year and resolving 196 (73.24%) within 20 working days, against a 95% target. The monitoring officer attributed delays to an uptick in the length and complexity of requests. The council leader criticised the number of 'frivolous' requests and specifically councillors submitting lengthy AI-generated FOI requests instead of asking officers or cabinet members directly.
Why it matters
Gives a measured on-time rate against target for one council where officials attribute slippage partly to AI-generated requests, a concrete data point for the archived records-request strain thread. Published Nov. 6 and not considered in the Nov. 7 edition.
Evidence and measured results
Local Democracy Reporting account of a public committee meeting with council-reported quarterly figures; the share of AI-generated requests is not quantified.
Limitations and uncertainty
Single quarter, single council; AI attribution is officials' opinion; 'frivolous' is a political characterisation; UK FOI regime differs from U.S. state public records laws.
Put this evidence to work
Lighthouse Advisory interpretation, grounded in this source. Enriched 2026-11-09; this does not change the original publication date. Each role follows the same checklist so takeaways compare across sources.
Sales
Role takeaway
- Customer problem
- FOI on-time performance falling well below target as requests grow longer and more complex.
- Stakeholders
- Monitoring officer
- Information governance team
- Governance and audit committee
- Council leader
- Discovery questions
- Do you record request length or complexity?
- How many requests come from internal members?
- What share is suspected AI-generated?
- Value hypothesis
- Measured workload data plus member protocols may recover on-time performance; unproven.
- Potential engagement
- A one-quarter records-workload baseline with complexity tagging.
- Unsupported claims
- That AI caused the shortfall
- Benefit of AI triage
- Any national trend from one council
Pre-sales engineering
Role takeaway
- Fit
- Fits records teams with statutory deadlines that need evidence on what is driving delay.
- Architecture and integration
- Case-management fields for request length, distinct asks, requester category and stage timing.
- Prerequisites
- Consistent request logging
- Agreed complexity categories
- Quarterly reporting
- Constraints
- Statutory 20-working-day deadline
- Requester-blind processing
- Small team capacity
- Security
- Ensure requester-category tagging does not breach requester-blind handling or data protection.
- Proof of value
- Complexity data explains slippage
- Internal-request share measured
- On-time rate trend by category
Delivery
Role takeaway
- Work
- Instrument FOI handling and set member information protocols.
- Dependencies
- Case-management system
- Group leaders' agreement
- Committee reporting cycle
- Ownership
- Monitoring officer and information governance team.
- Skills and adoption
- Train officers on consistent tagging and on clarifying overly broad requests.
- Governance checkpoints
- Committee review each quarter
- Member protocol agreed
- Data protection check on tagging
- Acceptance criteria
- Complexity recorded on all requests
- Internal FOIs reduced after protocol
- Quarterly on-time rate reported vs 95%
- Risks
- Political framing distracts from data
- Tagging overhead
- Attribution to AI without evidence
Implementation considerations
Lighthouse Advisory interpretation across the operating dimensions a public-sector buyer must settle before this evidence becomes a design. Each note answers the question under its heading for this specific source.
Architecture and integration
What must connect, and where does the AI sit in the workflow?
No technology change described; implies need for request tracking that records length/complexity and requester type.
Governance
Who approves, reviews and stays accountable for outcomes?
Raises internal governance questions when elected members use FOI (and AI) instead of member-officer information routes.
Security and privacy
What data, permissions and controls need testing?
None described.
Accessibility and workforce
Who is affected, and what skills or accommodations follow?
Officer capacity strained by request complexity; no staffing changes reported.
Procurement
What should contracts, pricing and exit terms secure?
None described.
Operating model
Which teams own the service once it runs?
Suggests diverting member information requests to internal channels and measuring request complexity alongside volume.
Publication history
Read preserved resource versions (JSON)Stable resource ID: south-kesteven-dc-foi-ai-requests-73pct-on-time-q2-20261106