Barry Phillips (CEO) BEM founded Legal Island in 1998. Since then, the company has become the leading workplace compliance training company in the island of Ireland. He was awarded a British Empire Medal in the New Year’s Honours List 2020 for services to employment and equality.
Barry is a qualified barrister, coach and meditator and a regular speaker both here and abroad. He also volunteers as mentor to aspiring law students on the Migrant Leaders Programme.
Barry is an author, releasing his latest book titled 'Mastering Small Business Employee Engagement: 30 Quick Wins & HR Hacks from an IIP Platinum Employer' in 2020 along with Legal Island MD Jayne Gallagher.
Barry has worked at the European Parliament, the European Court of Human Rights and the International Labour Organisation in Geneva before qualifying as a lawyer in 1993.
He has travelled extensively and lived in a total of eight different countries considering himself to be a global citizen first, a European second and British/Irish citizen last of all. His guiding mantra in life is “Never react but respond. Get curious not furious.”
Barry is an Ironman and lists Russian language and wild camping as his favourite pastimes.
This week Barry Phillips takes a look at the critical findings from Deloitte’s Tech Trends 2026 report
Transcript:
Hello Humans!
And welcome to the weekly podcast that aims to summarise in five minutes or less an important AI issue relevant to HR and the world of work. My name is Barry Phillips.
Last week we received Deloitte’s Annual Tech Trends report creatively entitled “Tech Trends 2026”.
Is this the last AI tech report of 2025? Possibly not. It seems we’ve had a report published just about every week this year and we’ve still got two weeks to go.
However, it could be the most important report of the year highlighting clearly how organisations are using AI successfully and how some are not.
In 2025, the big business lesson on AI was that you don’t get transformation by bolting a chatbot or a few “agents” onto the side of the company and hoping for magic; you get it by redesigning the work itself. The organisations seeing real returns rebuilt the plumbing and the playbook: they modernised legacy systems, made data usable, put governance around systems that can take actions, and designed workflows that assume AI can run continuously and at scale. That shift also changes people’s jobs — less repetitive execution, more oversight, risk/control, and improving the system — because AI works best when the whole operating model is built for it, not when it’s jammed into yesterday’s process.
A practical way to think about it is: AI success is an organisational change project wearing a technology hat.
Most failures weren’t because the models were “too dumb”, but because companies tried to automate messy, fragmented processes with brittle systems and unclear ownership.
The smarter approach in 2026 is to pick a few high-value domains, design them end-to-end for human + digital workers, measure outcomes (time, cost, quality, risk), and only then scale with multiple specialised agents that are orchestrated and monitored — because one “do-it-all” agent is usually just a new way to create chaos faster
Until next week. Bye for now