Poor quality data, legacy IT systems and skills shortages are among a raft of ‘significant challenges’ to AI adoption by the public sector, a group of MPs has warned.
Government plans to embrace the technology to drive efficiency and improve public services will not be realised unless systemic issues relating to out-of-date software platforms can be addressed.
The influential Public Accounts Committee at Westminster today warned that over a quarter of government IT systems are ‘either end of life’ or ‘impossible to update’ – and risk holding back plans to scale up AI across the public sector. It remarked also that for AI to work, it needs reliable, high quality data for algorithmic training purposes.
Unless ‘remediation funding’ is made available to plug critical digital infrastructure gaps, the government’s recent commitment to an AI revolution in public services could be seriously jeopardised, the MPs warned in a new report.
Sir Geoffrey Clifton-Brown MP, Chair of the Committee, said: “The government has said it wants to mainline AI into the veins of the nation, but our report raises questions over whether the public sector is ready for such a procedure. The ambition to harness the potential of one of the most significant technological developments of modern times is of course to be welcomed. Unfortunately, those familiar with our committee’s past scrutiny of the government’s frankly sclerotic digital architecture will know that any promises of sudden transformation are for the birds.
He added: “A transformation of thinking in government at senior levels is required, and the best way for this to happen is for digital professionals to be brought round the top table in management and governing boards of every department and their agencies. I have serious concerns that DSIT does not have the authority over the rest of government to bring about the scale and pace of change that’s needed. We hope the recommendations in our report aid the government in succeeding in bringing public sector systems into the 21st century for their users, where other efforts have failed.”
According to the report, an estimated 28% of central government systems met the definition last year of being “an end-of-life product, out of support from the supplier, [and] impossible to update…”.
Approximately a third of government’s 72 highest-risk legacy systems still lack remediation funding. The report warns that there are “no quick fixes here”, and calls for funding for the remediation of this kind of technology to be prioritised.
The report further finds slow progress in ensuring transparency in how AI is used by Departments. This jeopardises public trust in its use – key to its successful adoption. By January 2025, only a relative handful of records had been published on a government website set up to provide greater transparency on algorithm-assisted decision-making. The committee is calling on government to address public concerns over the sharing of sensitive data in AI’s use.
The government also has a long way to go to ensure a thriving market for AI suppliers, the MPs note. The PAC’s inquiry highlighted concerns that the dominance of a small number of large technology suppliers in the AI market risks ‘stifling competition and innovation’. The government’s approach to procurement also risks over-reliance on the services of specific companies, and an ‘inability to adapt’.
Persistent skills shortages were also highlighted. Around half of roles advertised in civil service digital and data campaigns went unfilled in 2024, and 70% of government departments report difficulty recruiting and retaining staff with AI skills. The PAC said it was also sceptical that the Department for Science, Innovation and Technology’s (DSIT) planned digital reforms will address the problem.
The committee welcomed the recent creation of a new digital centre of government within the department, but has ‘serious concerns over whether DSIT has sufficient leverage to drive change across the public sector’. The committee’s report is calling for a senior digital officer to be embedded at the top table with senior management at every department, on the boards at each department, and their respective agencies.
Some of the committee’s recommendations include:
Within six months, DSIT should set out publicly how it intends to:
a. Prioritise and ensure funding for the remediation of the highest–risk legacy technology
b. Establish an approach for measuring the costs associated with addressing legacy technology, as well as the costs of failing to act, to increase transparency and improve decision making
c. Track funding allocated for remediation work and take action where progress is slow
d. Address the risks to AI adoption resulting from barriers to data–sharing and poor data quality
