Financial services firms are adopting AI faster than ever, yet many risk diluting what makes them distinctive. According to Thomson Reuters’ AI Adoption Reality Check (June 2025), firms with a defined AI strategy are twice as likely to see revenue growth as those experimenting without one. The challenge isn’t whether to adopt AI, but how to do so without losing the trust, tone and authenticity your clients recognise.
Your firm’s voice has taken years to build. With the right approach, AI can strengthen it while freeing teams to focus on higher-value work.
Here’s how leading firms are achieving both.
Start with Your Templates
Preserving your firm’s tone starts with your existing materials. Instead of relying on generic outputs, upload approved templates, frameworks and document libraries directly into the system.
It works. One 200-adviser network using automated suitability report generation cut report creation time from 105 minutes to just 15 without losing the firm’s signature phrasing or formatting. The secret was simple: they began with their own templates, ensuring every output reflected established standards.
By grounding AI in your own documentation, the system learns your language from day one. Disclaimers, tone and compliance wording stay consistent, while advisers focus on client-specific details.
Build Governance Into the System
Governance separates scalable AI adoption from short-lived pilots. Role-based permissions let compliance teams lock critical content while advisers personalise client details, ultimately combining control with flexibility.
Governance also depends on visibility. When every generated line can be traced back to its data source, reviewers gain confidence that communications meet firm standards. According to IIF-EY’s 2025 AI/ML in Financial Services report, 88% of firms now use generative AI, up from 52% the year before. The ones seeing success are those that built strong governance frameworks early.
Clarification prompts play an important role, too. Instead of filling gaps with assumptions, the system flags missing data and asks advisers to confirm it. This keeps documents accurate and prevents generic, off-brand language from slipping through.
Train Your Team on Voice Guidelines
AI reflects the quality of the input it receives. Vague notes produce vague outputs. Trinetix’s 2025 research found that many firms underestimate the behavioural and cultural change required to use AI responsibly.
Effective training helps advisers understand when to review, edit and override automated content. The aim is not replacement but amplification. When teams apply voice guidelines consistently, every document reads as if your firm wrote it.
Build With Users, Not Just For Them
The most effective AI systems are built with the people who use them every day. When advisers are involved in shaping features and workflows, the result feels intuitive rather than imposed.
This collaborative approach helps AI understand how real work happens. Advisers think in sequences, not software screens. They move from client conversation to context to documentation. Tools designed around that flow feel natural to use and make it easier to preserve the firm’s voice.
User involvement also uncovers the small details that matter most. Advisers often spot subtle phrasing or context cues that affect how authentic outputs sound. Capturing that insight early allows teams to refine systems before rollout, ensuring smoother adoption and stronger results.
→ Read how Aveni builds products with advisers through the Champions Network
Use Domain-Specific AI Models
Generic models can write, but they rarely understand the language of financial services. Without deep knowledge of industry terminology and regulation, they risk producing content that sounds polished but misses crucial nuance.
Domain-specific models, trained on financial data and documentation, understand the difference between Consumer Duty and customer care. They know when to use technical language and when to simplify for clarity.
In 2024, FCA fines tripled to £176 million, while a majority of UK financial firms cited safety and security as their main AI adoption barrier. Firms using financial-services-specific models reduce these risks by choosing systems built with regulatory context at their core.
→ See how FinLLM builds AI safety into financial services whilst maintaining regulatory alignment
Test and Refine Continuously
Preserving your firm’s voice is an ongoing process. As your standards evolve, your AI should evolve too. Regular reviews of generated content help identify when tone, terminology, or accuracy begin to drift.
Gartner predicts that by the end of 2025, 30% of generative AI projects will be abandoned after proof of concept due to poor data quality, rising costs, or unclear value. The firms that succeed are those that treat AI as a living system. They treat it as one that improves through continuous testing and feedback.
Encourage advisers to share where outputs feel authentic and where they need refinement. Feed that insight back into your templates and training data. Over time, your firm’s voice becomes stronger, more consistent, and easier to scale.
→ Explore how AI implementation frameworks help firms scale beyond pilots whilst maintaining standards
The Efficiency Payoff
When firms achieve the right balance between authenticity and automation, the results are clear. The same 200-adviser network that cut report creation time from 105 to 15 minutes saved 15,000 hours a year and reduced costs by around £450,000.
Those hours went back into what matters most: client conversations, strategic planning, and relationship building. The efficiency gains are real, and they come without compromising the voice that defines your firm.
Your firm’s voice took years to build. AI should strengthen it, not replace it. With the right strategy, you can keep your communications authentic while capturing the efficiency gains that drive your business forward.
Discover how your firm can preserve its voice while scaling with AI. Book a demo with Aveni →
