TECHNOLOGY
AI impact on NHS estates policy and workforce
NHS capital, estates and facilities teams are juggling ageing infrastructure, tightening budgets, and rising regulatory expectations. Here, Dr Carl-Magnus von Behr, co-founder and director of CompliMind (formerly
Innex.AI), brings together two practitioner perspectives on the practical role of AI in everyday estates work. Paul Luxton, head of Acute Estates and Infrastructure at Somerset NHS Foundation Trust, shows how AI can bring clarity and consistency to policy reviews. Paul Boocock, director of Estates and Facilities at University Hospitals Birmingham NHS Foundation Trust, reflects on how the same tools can support efficiency, governance, and workforce development at scale.
High-quality healthcare facilities underpin safe care, staff wellbeing, and operational resilience. Yet a large share of the NHS estate is ageing, and the maintenance backlog has climbed to £13.8 bn across England.1 The post-Grenfell regulatory landscape has intensified compliance requirements, demanding more rigorous documentation, reporting, and assurance processes from already stretched teams. Workforce pressures compound the risk:
around 34 per cent of the Estates and Facilities Management (EFM) workforce are aged 55 or older.2
The pressure on the workforce is already
showing, with sickness absence in March 2025 averaging 6.57% for ‘hotel, property & estates’, higher than the 4.24% rate for ‘professionally qualified clinical staff’.3 To overcome these challenges, EFM teams need
protected time to reflect, collaborate and innovate. However, time is the scarcest resource. As shown in Figure 1, EFM staff spend about 9.6 hours each week searching for information, 3.7 hours reviewing, and 8.7 hours writing compliance and assurance documents.4
That is over
22 hours a week, close to 60% of a 37.5-hour week, absorbed by paperwork rather than planning, engineering and problem-solving. The opportunity is to streamline how staff find, assemble and check information so more of their expertise is applied to improving the estate. Against this backdrop, the following two frontline accounts explore how estates-specific AI can help. Paul Luxton (Somerset) focuses on improving clarity and consistency in policy review, and Paul Boocock (UHB) lifts the view to system-level efficiency, governance, and workforce development.
From complexity to clarity: How AI is transforming risk and compliance Paul Luxton says: “Anyone who’s spent more than a few days in NHS estates will know the feeling: you open one guidance document to check a compliance point, only to find it refers you to another, which points to a third…and before you know it, you’re knee-deep in cross-references that don’t quite line up. “The Building Safety Act alone cites over 146 separate documents. Add in Building Safety Regulator frameworks, HTMs, HBNs, British Standards, and Trust policies, and you’ve got a compliance landscape that’s anything but joined-up. Each document has merit, but together they can pull in different directions, making consistent application a real headache.
“As a head of Acute Estates, with specialist knowledge in various EFM topics, especially fire safety, water safety, and energy management, I’ve spent years chasing down the ‘right’ reference, reconciling conflicts, and ensuring our CAFM data reflects what’s actually happening on the ground. Too often it’s felt like navigating a system designed to challenge us, rather than support us. I’ve had to piece things together the hard way, and I’m determined that embedding consistency of information will support future colleagues to not repeat that journey.
Bringing order to the paperwork puzzle “It’s exactly because of this fragmented landscape that I’ve become an early supporter of the CompliMind platform. What sets it apart is its ability to draw together regulations that normally sit in isolation, and present them in a way that’s directly usable in our day-to-day documents. “Instead of leafing through a dozen PDFs, or pausing
mid-draft to check an acronym, I can drop a policy or SOP into CompliMind and get structured, contextual feedback. It tells me if the right regulations are referenced, if responsibility allocation is clear, and whether the language stands up to scrutiny under the Building Safety Act. “This isn’t just a fancy search tool. CompliMind
understands the relationships between different standards – whether that’s HTM 05-01, the Fire Safety Order, or Trust procedures – and highlights what’s missing, inconsistent, or needs tightening up. For me, it’s like having a compliance colleague with an encyclopaedic memory, who can recall the exact clause you need, the moment you need it. “The real game-changer has been the CompliMind
Review Assistant. This isn’t just scanning documents or pulling out keywords – it actively evaluates drafts for compliance, showing exactly where an issue lies, which standard it links to, and why it matters. This isn’t ‘AI replacing expertise’. It’s AI augmenting our work – speeding up the review process without sacrificing rigour.
October 2025 Health Estate Journal 99
Figure 1: The web of inputs estates teams must reconcile every week: legislation, codes of practice, technical standards, health and safety, contracts, local policies, and manuals.
Page 1 |
Page 2 |
Page 3 |
Page 4 |
Page 5 |
Page 6 |
Page 7 |
Page 8 |
Page 9 |
Page 10 |
Page 11 |
Page 12 |
Page 13 |
Page 14 |
Page 15 |
Page 16 |
Page 17 |
Page 18 |
Page 19 |
Page 20 |
Page 21 |
Page 22 |
Page 23 |
Page 24 |
Page 25 |
Page 26 |
Page 27 |
Page 28 |
Page 29 |
Page 30 |
Page 31 |
Page 32 |
Page 33 |
Page 34 |
Page 35 |
Page 36 |
Page 37 |
Page 38 |
Page 39 |
Page 40 |
Page 41 |
Page 42 |
Page 43 |
Page 44 |
Page 45 |
Page 46 |
Page 47 |
Page 48 |
Page 49 |
Page 50 |
Page 51 |
Page 52 |
Page 53 |
Page 54 |
Page 55 |
Page 56 |
Page 57 |
Page 58 |
Page 59 |
Page 60 |
Page 61 |
Page 62 |
Page 63 |
Page 64 |
Page 65 |
Page 66 |
Page 67 |
Page 68 |
Page 69 |
Page 70 |
Page 71 |
Page 72 |
Page 73 |
Page 74 |
Page 75 |
Page 76 |
Page 77 |
Page 78 |
Page 79 |
Page 80 |
Page 81 |
Page 82 |
Page 83 |
Page 84 |
Page 85 |
Page 86 |
Page 87 |
Page 88 |
Page 89 |
Page 90 |
Page 91 |
Page 92 |
Page 93 |
Page 94 |
Page 95 |
Page 96 |
Page 97 |
Page 98 |
Page 99 |
Page 100 |
Page 101 |
Page 102 |
Page 103 |
Page 104 |
Page 105 |
Page 106 |
Page 107 |
Page 108 |
Page 109 |
Page 110 |
Page 111 |
Page 112 |
Page 113 |
Page 114 |
Page 115 |
Page 116 |
Page 117 |
Page 118 |
Page 119 |
Page 120 |
Page 121 |
Page 122 |
Page 123 |
Page 124 |
Page 125 |
Page 126 |
Page 127 |
Page 128 |
Page 129 |
Page 130 |
Page 131 |
Page 132 |
Page 133 |
Page 134 |
Page 135 |
Page 136 |
Page 137 |
Page 138 |
Page 139 |
Page 140 |
Page 141 |
Page 142 |
Page 143 |
Page 144 |
Page 145 |
Page 146 |
Page 147 |
Page 148 |
Page 149 |
Page 150 |
Page 151 |
Page 152 |
Page 153 |
Page 154 |
Page 155 |
Page 156 |
Page 157 |
Page 158 |
Page 159 |
Page 160 |
Page 161 |
Page 162 |
Page 163 |
Page 164 |
Page 165 |
Page 166 |
Page 167 |
Page 168 |
Page 169 |
Page 170 |
Page 171 |
Page 172 |
Page 173 |
Page 174 |
Page 175 |
Page 176 |
Page 177 |
Page 178 |
Page 179 |
Page 180 |
Page 181 |
Page 182 |
Page 183 |
Page 184
