Tech, Talent, and Trust: Key Takeaways from Accountancy Age’s 35 Under 35 2026 Celebration

Tech, Talent, and Trust: Key Takeaways from Accountancy Age's 35 Under 35 2026 Celebration

Key takeaways from the Accountancy Age's 35 Under 35 2026 Celebration: Why AI requires clean data, how apprenticeships widen access, and the human skills reshaping UK accounting firms.

At yesterday’s annual Accountancy Age 35 Under 35 Celebration, hosted in partnership with AJ Chambers, we brought together the UK’s most forward-thinking practice leaders, tech strategists, and rising talent to address two intertwined forces redefining our industry: the rapid acceleration of AI and the changing dynamics of early-career recruitment.

Opening the afternoon, Bryan Glick, VP, International at Informa TechTarget, welcomed guests to celebrate the Class of 2026. The event featured a keynote from James Gosling, Managing Director at AJ Chambers, alongside two high-impact panel sessions moderated by Bryan Glick and Tim Keech, Associate Divisional Director of Tax Recruitment at AJ Chambers.

Panel 1 | AI & Tech: Will it replace accountants?

1. Current Practice Adoption & The Unstructured Data Drain

Mark Parr (Partner Head of Technology, Buzzacott), Natasha Millward (Client Services Director, DJH), and James Sundin (Co-Founder, Represent Group) explored the reality of tech adoption on the ground.

UK practices are securing immediate returns on administrative tasks, but broader Large Language Model (LLM) deployment faces operational friction:

Adoption Stage Focus Areas Key Characteristics
High Adoption &
High ROI
Meeting transcriptions, client onboarding workflows, draft consolidation notes Reduces administrative churn; yields immediate time savings for fee-earners.
Emerging &
High Friction
AI embedded across vendor toolkits, LLM deployment over siloed databases Increases software licensing fees; risks repeating errors across messy data.

Widespread vendor deployment has introduced fresh financial friction, as software providers pass R&D costs back to practices through higher licensing fees. To manage costs, leading firms are running targeted steering groups to test tools on specific operational bottlenecks before full rollout.

James Sundin highlighted the fundamental distinction between deterministic automation and probabilistic AI:

Category Primary Function Technology Required Operational Impact
Deterministic
Automation
Moving structured data from Database A to Database B Standard APIs, programmatic transfers, rule-based workflows Requires zero AI; resolves manual re-keying efficiently.
Probabilistic
Processing
Synthesising unstructured narrative data and finding patterns LLMs and probabilistic AI agents Fails over messy databases; requires clean data architecture.

Most UK practices maintain disconnected software platforms across CRM, audit, tax, and billing. Moving structured data between systems requires clean API integration, not AI. Deploying LLMs over unstructured data leads to unreliable outputs, amplified client portfolio risk, and wasted billable hours spent cross-checking information.

2. Protecting Quality, Managing Risk, and the “Three-Tiered Firm”

Bypassing human review to meet tight delivery windows creates severe professional risk. Junior staff who over-rely on automated tools without understanding underlying tax legislation lose the ability to spot structural errors.

Practices must establish three essential risk pillars:

  • Cybersecurity: Protecting client records, personal identifiers, and strict data privacy.
  • Data Governance: Assigning dedicated leads to monitor privacy, access rights, and database integrations.
  • Quality Control: Restricting AI tools to query authoritative, verified accounting libraries, with mandatory human-in-the-loop review.

The panel rejected the concept of an “AI replacement apocalypse,” projecting a shift toward a three-tiered operating model:

Firm Tier Core Responsibilities Primary Operational Focus
1. Front Office
(Client Experience & Advisory)
Commercial partners, relationship leads, strategic advisors Human trust, commercial strategy, empathetic advice, relationship building.
2. Human Back Office
(Verification & Quality)
Technical specialists, reviewers, model trainers Reviewing agent outputs, handling edge cases, ensuring technical compliance.
3. Digital Back Office
(Automated Execution)
AI agents, automated bots, integrated software tools Processing raw data, generating draft reports, executing routine admin.

Panel 2 | “How can we broaden access into the accountancy profession?”

Panel 2, moderated by Tim Keech, featured Gareth John (Policy Director, First Intuition), Oliver White (Audit Director and Technology Lead, Affinia), and Lucy Cohen (Founder and CEO, Mazuma).

1. The Apprenticeship Advantage: Behaviours Over Textbooks

Gareth John noted that the true value of modern apprenticeships lies in the Knowledge, Skills, and Behaviours (KSBs) framework. While software handles technical knowledge, apprenticeship routes teach communication, active problem-solving, and critical reasoning from day one.

2. What Modern Employers Seek: Curiosity and Emotional Intelligence

Lucy Cohen and Oliver White emphasised that academic degree classifications (such as 2:1 or First-Class honours) are no longer the primary hiring benchmark:

Hiring Criteria Traditional Mindset Modern Practice Benchmark
Academic
Background
Strict degree classifications (2:1 or First-Class) Focus on aptitude, curiosity, and non-traditional entry points.
Core
Competency
Pure technical competency and textbook knowledge High Emotional Intelligence (EQ), interpersonal rapport, communication.
Commercial
Aptitude
Passive execution of assigned compliance tasks Active problem-solving mindset (asking “why” behind numbers).
Tenure
Expectations
Expecting long-term 15-year tenure from day one Building adaptable skills and accepting fluid career mobility.

Cohen highlighted that firms need trainees who notice underlying patterns and ask probing questions; for instance, identifying why a client unexpectedly requests three years of accounts and flagging potential commercial drivers. White added that technical rules are easily taught, whereas natural EQ and client rapport cannot be automated.

3. Pipeline Responsibility & Career Advice

Addressing employer concerns regarding trainee retention, the panel’s consensus was clear: train them anyway. Investing in early-career pipelines builds long-term industry capacity and creates lifelong brand advocates.

For rising accountants navigating qualification, the panel shared four core principles:

  1. Reframe Failure as Growth: View exam or technical setbacks as natural learning milestones.
  2. Distinguish Pressure from Burnout: Differentiate healthy deadline pressure from toxic stress.
  3. Channel Imposter Syndrome: Recognise feeling out of your depth as a sign of professional growth.
  4. Build Networks Early: Prioritise face-to-face networking to develop long-term commercial relationships.

Key Findings & Conclusion

Yesterday’s discussions reinforce that the UK accountancy profession is undergoing an operational evolution rather than a sudden existential disruption:

  • Clean Architecture Trumps Tech Hype: AI tools depend entirely on the quality of underlying databases. Centralising data architecture and separating basic API automation from probabilistic AI prevents ballooning costs and system errors.
  • Human Advisory Commands the Highest Premium: As compliance moves to the digital back office, trusted client relationships, active listening, and empathetic advisory remain a firm’s primary competitive advantage.
  • Pipeline Investment Is Essential: Widening access through apprenticeships, prioritising emotional intelligence over rigid academic metrics, and fostering resilience in early-career talent are critical steps to closing the industry’s skills gap.
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