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Bloor Research Change is inevitable. At Bloor, we do not simply adapt; we provoke it.

We actively challenge assumptions, consistently pushing organisations to improve and succeed. Bloor Research is one of Europe's leading independent IT research, analysis and consultancy organisations. We explain how to bring greater agility to corporate IT systems through the effective governance, management and leverage of Information. We have built a reputation for 'telling the right story' with independent, intelligent, well-articulated communications content and publications.

October's First Friday Newsletter is here.In this edition:🔹 Entuity Software (Park Place Technologies), by Paul Bevan: o...
02/10/2026

October's First Friday Newsletter is here.

In this edition:

🔹 Entuity Software (Park Place Technologies), by Paul Bevan: one view, every network. A vendor-agnostic platform that brings multi-vendor, virtual and cloud environments together in one place.

🔹 When EBITDA Lies: Why the Metric Fails for Banks, by Darren Sack: what Lloyds' £2bn savings ambition reveals about AI transformation, and the unquantified risks behind the headline number.

🔹 Is AI Productivity a Myth?, by Bloor Research: how the Fusion Economy turns owned expertise into lasting value and new income.

🔹 ParkView Asset Intelligence™, by Paul Bevan: AI-powered insights for proactive maintenance and smarter hardware refresh decisions.

🔹 90% of Your People Have a Job Description That Doesn't Describe Their Job, by Cheney Hamilton: why mapping real outcomes helps HR and operations make better automation decisions.

🔹 Generative AI vs Digital Twin: What Both Miss, by Bloor Research: both solve different problems, but neither preserves a person's expertise.

🔹 Capability Headcount, by Nico Decock: BPO contract value fell 14% at steady activity. Capability is coming loose from headcount.

📅 Plus two events: Daniel Howard on the last manual step in AI-assisted testing (K2view, Oct 8), and the Bloor team at UNLEASH Paris 2026 (Oct 20–22) on digital twins and the future of work.

Read the full edition 👇
https://mailchi.mp/bloor/welcome-to-the-october-edition-of-first-friday

Lloyds has priced its AI benefit to the exact pound. It has priced the risk of that AI at zero. Not a low number, no num...
02/10/2026

Lloyds has priced its AI benefit to the exact pound. It has priced the risk of that AI at zero. Not a low number, no number at all.

That's the gap Darren Sack opens up in his new banking paper for Bloor Research. For a bank, EBITDA measures nothing, because the things it strips out (interest, depreciation) are the business itself. So you have to read the gauges that actually matter: cost-to-income ratio, net interest margin and the provision lines. Read that way, Lloyds' half-year is genuinely strong, with return on tangible equity up to 17.1% and cost-to-income down to 50.4%.

But its £2bn AI-led savings programme doesn't quite add up. The cost line moved just £2m over twelve months, so the improvement came from rising income, not falling cost. The staff-cost "reduction" turns out to be a severance-timing effect, while salaries actually rose 4%. And while the benefit of AI has a precise number (over £100m in 2026, £2bn by 2030), the risk of it has none: no provision for AI governance or model risk, and the same empty row across Lloyds, NatWest and Barclays.

Banks know what a late provision looks like. Lloyds carries £1.95bn against motor-finance conduct that arrived years after the fact. As Darren shows, the benefit of the technology has a number, the risk of it doesn't. That asymmetry is the finding.

📖 Read Darren's full banking paper 👇
https://www.bloorresearch.com/when-ebitda-lies-banking-lloyds-labour-debt/

Most enterprise networks aren't built from one vendor, so why monitor them with one vendor's tools? That's the question ...
02/10/2026

Most enterprise networks aren't built from one vendor, so why monitor them with one vendor's tools? That's the question Paul Bevan takes on in his latest Bloor Research review. A typical estate runs Cisco switches, Juniper or Palo Alto firewalls, Arista or HP gear, VMware and Hyper-V, with workloads across AWS and Azure, and monitoring that with a separate tool for each ecosystem is how visibility gaps open up.

Entuity Software™ from Park Place Technologies takes a different approach: vendor-agnostic monitoring that discovers, maps and visualises the whole estate from one interface, with support for thousands of devices across hundreds of vendors and event management that cuts alert noise by up to 99%.

The new V23.0 release adds a lightweight remote agent for sites beyond the network perimeter, credential-free host polling that keeps admin credentials out of the central server, streaming telemetry via Telegraf for hundreds more asset types, and GPU coverage for Nvidia, AMD and Intel for the AI era. Backed by Park Place's insight from 25,000+ customers across 180 countries, Entuity helps IT teams shift from reactive firefighting to proactive, predictive operations.

📖 Read the full review 👇
https://www.bloorresearch.com/research/entuity-software-park-place-technologies-oct-2026/

Your income has a ceiling, and it's your own calendar.If your professional value comes from what you know, you already k...
30/09/2026

Your income has a ceiling, and it's your own calendar.

If your professional value comes from what you know, you already know the constraint: decades of pattern recognition, locked inside one person's diary, sold one hour or one engagement at a time.

It's not a niche problem. In the US alone, 5.6 million independent workers now earn six figures or more solo, nearly double the 3 million recorded in 2020. That's a fast-growing group of consultants, experts, and founders whose entire income depends on their own accumulated judgement, rationed by the hours in a day.

That's exactly who Digital Me is built for. The Subject Matter Expert whose supply constraint it removes. The Consultant whose Digital Me delivers a first cut before they enter the room. The Founder who is the product, and whose asset it protects if they exit or step back. The Thought Leader who can amplify reach without spending more time. And the thought-leadership case is measurable: 65% of decision-makers trust it over marketing materials, and 79% of hidden decision-makers are more likely to back a vendor in an RFP when they produce it consistently.

The bottleneck was never whether thought leadership works. It's whether one person can keep producing enough of it without it eating every hour left for the work that pays. A captured, owned asset compounds. Billable hours don't.

📖 Read more: https://www.bloorresearch.com/digital-twin-for-executives-consultants-thought-leaders/

Gartner predicts 40% of agentic AI projects will be cancelled by 2027, and not because the models are too weak. Because ...
29/09/2026

Gartner predicts 40% of agentic AI projects will be cancelled by 2027, and not because the models are too weak. Because they were built on nothing in particular.

"Build your own AI" usually means one of three things: an agent platform, a no-code model builder, or a from-scratch coding project. All three work. But none of them answer the only question that determines whether the result is any good: built on what? A platform gives you the scaffolding - it doesn't give you the material. Gartner's own reasons these projects die (cost, unclear value, weak governance) usually trace back to a system built before anyone worked out what it was supposed to know.

Bain makes the same point from the other side: frontier models are commoditising fast, so the durable advantage is whatever a competitor can't copy - the proprietary knowledge only you have. A tool built on borrowed intelligence is just a generic model with your logo on it.

The real build is five stages, in order: Capture your reasoning, Codify it into a private intelligence layer, Deploy it, let it Compound with every use, and Own the whole thing. Most attempts skip straight to Deploy, which is exactly why they're so easily replaced. The hard part is Capture, because expert knowledge is mostly tacit and lives in experience, not documents. But that's the whole point: capture it before it's lost, and you get a system built around your own judgement - not a chatbot wearing your name.

📖 Read more: https://www.bloorresearch.com/build-your-own-ai/

Most companies add "human oversight" to their AI to make it trustworthy. They've got it backwards.In most enterprises, t...
25/09/2026

Most companies add "human oversight" to their AI to make it trustworthy. They've got it backwards.

In most enterprises, the human was added after the AI was built, a reviewer bolted onto a system designed without them. And often not by choice: the EU AI Act's Article 14 requires human oversight for high-risk AI, so "human-in-the-loop" frequently exists to satisfy a regulation, not because anyone designed around a person from the start. That's not trust, it's a compliance checkpoint.

Even Stanford's own research community pushed back on the framing. As they put it at their 2022 conference: "Humans are not simply 'in-the-loop.' Humans are in charge; AI is 'in-the-loop.'"

The distinction runs deep. AI built to imitate a person fits the human around it afterward as a checkpoint - trust bolted on, displacement the logical outcome. AI built from a specific person's own knowledge makes the human the origin, not a reviewer - so trust is structural, built in from the first design decision.

So for anyone evaluating AI, there's one practical test: where in the build process does the human actually show up? You can't inspect trust into a system that was designed without you.

Read more: https://www.bloorresearch.com/human-in-the-loop-ai/

"You won't lose your job to AI. You'll lose it to someone who uses AI." You've probably heard it and the data says it's ...
24/09/2026

"You won't lose your job to AI. You'll lose it to someone who uses AI." You've probably heard it and the data says it's only half true.

Goldman Sachs estimates AI is eliminating roughly 16,000 net US jobs a month in 2026, about 192,000 over the past year. And it isn't spread evenly: Stanford's 2026 AI Index found employment for software developers aged 22–25 has fallen nearly 20% since 2024, with younger workers facing displacement at close to three times the rate of those aged 40–55.

So "just learn to use AI" doesn't quite hold. The real dividing line is what a role is made of. Jobs built around a fixed script -transcribing, routing, processing, repeating; carry the highest substitution risk. Jobs built on judgement, accountability, and unstructured problems lean the other way. And being AI-fluent won't save you: roles requiring it grew from about 1 million to 7 million in two years. It's table stakes now, not protection.

What actually protects a job isn't avoiding AI, or even prompting it well. It's owning a structured, deployable version of your own expertise, the difference between being the task AI was built to replace and the person AI was built to extend.

📖 Read more: https://www.bloorresearch.com/ai-job-loss/

90% of people using AI are convinced it's saving them time. The measured reality? Just 2.8%.That's the finding from a st...
22/09/2026

90% of people using AI are convinced it's saving them time. The measured reality? Just 2.8%.

That's the finding from a study of 25,000 workers by economists at the Universities of Chicago and Copenhagen and a quarter of workers actually spent more time on the same tasks afterward. It's not a one-off, either: MIT found 95% of corporate AI investments show zero measurable return, Goldman Sachs put AI's contribution to 2025 US GDP growth at "basically zero," and Workday found 40% of the time AI saves is lost again to rework.

The common thread? None of that gain is owned by the person using the tool. The time saved vanishes the moment the session ends; nothing compounds, nothing is left behind.

But the bigger story isn't about chatbot speed at all. The World Economic Forum projects 22% of all jobs affected and 40% of required skills changing by 2030. The real question is who owns and redeploys their expertise as work restructures underneath them and who's left holding a skill set with a shrinking shelf life.

That's the Fusion Economy: building a durable, owned asset out of what you actually know, so it compounds instead of resetting to zero every session. The chatbot forgets you the moment you log off. Your expertise shouldn't.

📖 Read more: https://www.bloorresearch.com/is-ai-productivity-a-myth-fusion-economy/

The most valuable thing in your business just handed in its notice, and none of your systems know how to keep it.Every o...
18/09/2026

The most valuable thing in your business just handed in its notice, and none of your systems know how to keep it.

Every organisation eventually loses someone whose knowledge was never written down: the specialist who knew why a client relationship worked, the consultant whose judgement came from twenty years no manual ever captured. When they leave, that judgement leaves with them.

We reach for two tools to stop this, and neither was built for it. Succession planning decides who takes over, not what the outgoing person actually knew. Knowledge management stores documents and FAQs; it can hold a policy, but not the reasoning a 20-year specialist uses to decide when to break it.

The scale is the striking part: Bloor Research finds as much as 40 years of specialist knowledge can sit locked inside one expert's head, with no structure to capture it before they go.

The knowledge isn't gone. It's just never been made keepable.

That's the gap DigitalMe was built to close 👇

https://www.bloorresearch.com/institutional-knowledge/

Most companies rolling out generative AI assistants and digital twins are chasing the same thing: efficiency. Faster dra...
15/09/2026

Most companies rolling out generative AI assistants and digital twins are chasing the same thing: efficiency. Faster drafts, better predictions, fewer surprises on the factory floor. Both technologies deliver on that promise.

But neither one was built to hold onto something else entirely: the judgment a specific person built up over decades of doing a specific job. A digital twin can flag a machine part wearing down before it fails. It has no idea why a veteran engineer trusts her gut over the readout in certain edge cases. A generative AI assistant can write a polished summary in seconds. It has no idea what your team actually learned the hard way last year. As Bloor Research puts it, that kind of intelligence is synthetic, not sovereign; borrowed, not owned.

That gap gets expensive the moment someone retires or moves on. The knowledge doesn't transfer with a handover document; it just disappears, and the systems built to make the business faster suddenly can't explain why something went wrong or who to ask.

Bloor Research's latest piece argues for a different way of thinking about AI investment altogether: one where human expertise and digital tools stay in constant dialogue, where what people know gets captured, owned, and kept up to date rather than left to walk out the door.

So here's the real question for anyone about to sign off on the next AI rollout: are you building something that protects what only your people know?

Read more: https://www.bloorresearch.com/generative-ai-vs-digital-twin/

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