As Model Portfolio Services (MPS) continue to grow in popularity, the level of interest in this marketplace appears to show no end. With new entrants, product ranges, and tools launching regularly, competition and efficiencies are helping to drive down fees—benefiting both advisers and clients. While much of this efficiency may come from technology, firms are increasingly exploring the use of artificial intelligence (AI) to push these gains even further.

But how far should AI go in the MPS space? Which function in the MPS ecosystem will benefit the most from its use, and how will this impact the end client?   For now, we will explore how the roles of the discretionary fund manager (DFM) and financial adviser may be improved by the deployment of AI.

AI’s Advantages: Speed, Scale, and Precision

AI brings powerful capabilities to MPS overall. By instantly processing years of financial data, algorithms can help identify possible adjustments and courses of action to take in real time.

For DFMs specifically, that’s just the beginning:

  • Automation and consistency: AI can ensure that model portfolios stick to their target risk levels and rebalancing rules, avoiding the emotional pitfalls humans face. It helps remove spur-of-the moment decisions, keeping strategies disciplined and on course over time.
  • Scale and personalisation: AI can manage thousands of accounts simultaneously, handling routine tasks like portfolio monitoring and tax optimisation. Beyond MPS, it can also help tailor portfolios to individual preferences, timelines, and ESG values — integrating these into the portfolio construction process – for bespoke portfolio solutions.
  • Time savings: With AI handling data-heavy tasks, DFMs can focus on strategy and client relationships, working directly with advisers to drive the best outcomes. AI becomes the engine for reliable portfolio delivery, freeing time for more valuable human input.

The Human Element: Judgment and Trust

Despite AI’s strengths, human advisers remain vital. For financial advisers especially, the qualities they bring are hard to replicate:

  • Personal connection and trust: Clients value empathy and the assurance that a human understands and acts in their best interest. Trust remains one of the adviser’s most valuable assets.
  • Behavioural coaching: During market highs and lows, advisers help clients navigate emotional responses. AI may be immune to fear or greed, but it can’t coach someone through these emotions.
  • Context and insight: Markets are shaped by politics, culture, and events. Financial advisers can help interpret breaking news and use their experience to foresee potential impacts that are hard for algorithms to quantify. Advisers can also anticipate how regulation or tax changes might affect a client’s investment strategy.
  • Client-specific nuances: Every client’s situation is unique—inheritances, tax concerns, family dynamics. While AI personalisation is improving, it can overlook subtleties. Two clients with similar data may need very different advice—something a financial adviser can discern.

Limits of AI: Trust, Transparency, and Risk

AI brings a number of overall challenges that must be managed carefully:

  • Opacity (“black box” problem): Many AI models offer little clarity on how decisions are made. Clients may be uneasy trusting recommendations they can’t understand — a serious concern in a trust-based profession.
  • Errors and accuracy: AI is only as good as the data it receives. Bad inputs can lead to bad outputs, and the consequences in investing can be costly. As it relates to DFMs, human review can help catch issues that a model might miss.
  • Bias and conflicts of interest: AI reflects the data it’s trained on. If it relies heavily on proprietary research, it may unintentionally favour a DFM firm’s own products. This introduces potential conflicts that must be carefully managed by the DFM.
  • Privacy and security: AI requires large volumes of client data, raising concerns around data protection. Both DFMs and adviser firms must ensure robust cybersecurity and compliance with privacy laws like GDPR.

A Hybrid Future: Combining Strengths

Using our crystal ball, it’s likely that the future won’t be AI versus humans, but a partnership. A 2024 LSEG report predicts a “hybrid advisory model” where human expertise and AI work hand in hand. AI can serve as a high-powered assistant, rapidly crunching data and generating recommendations that both a DFM can review, and work with an adviser to find ways to tailor these to a client’s needs.

This model supports trust. Advisers can help explain AI-driven decisions, offer context, and reassure clients. Meanwhile, AI allows DFM firms to operate more efficiently, bringing down costs and freeing them to focus on client relationships and strategic thinking, working with advisers to deliver the best possible outcomes to clients.

Balance Over Replacement

AI continues to evolve and will play an increasingly central role in wealth management. But for now, it’s not a replacement for people. Trusted advisers bring experience, empathy, and judgment that clients depend on. AI delivers speed, consistency, and data power.

Industry surveys consistently show that clients value the efficiencies AI brings—but still want the human touch. The best approach blends both. In this model, AI isn’t a threat—it’s a tool. One that, when paired with human insight, helps deliver better, more trustworthy financial advice.

Professional Adviser article, 26 June 2025

MPS: Would you trust AI to replace human decision-making? (professionaladviser.com)