Artificial Intelligence in Valuation: Technology, Judgement, and Responsibility

AI in Valuation – Why the Ultimate Responsibility Still Lies with the Valuer

The valuation profession is undergoing a significant transformation with the rapid integration of Artificial Intelligence (AI), machine learning models, automated analytics, and technology-driven valuation platforms. From financial modelling and market benchmarking to predictive analytics and data extraction, AI is increasingly becoming a part of the valuation ecosystem.

Recognising this evolving landscape, the latest International Valuation Standards framework under IVS 104 has specifically addressed the use of AI and other technology-based tools in valuation engagements. While technology can substantially improve efficiency, scalability, and analytical capability, the standards make one principle abundantly clear:

The valuer remains ultimately responsible for the valuation conclusion and compliance with IVS.

AI in Valuation – A Powerful Tool, Not a Substitute for Judgement

Modern valuation engagements now involve the use of:

• AI-assisted market analysis,
• automated comparable company screening,
• data aggregation tools,
• predictive valuation models,
• algorithmic risk assessments,
• document intelligence and extraction systems.

These tools may operate using:

• transparent logic systems, where the methodology and decision-making process can be reasonably understood and verified; or
• opaque / non-transparent logic systems, often referred to as “black box” systems, where the rationale, pathways, or internal computations may not be readily explainable.

The revised IVS 104 acknowledges both categories. However, it unequivocally states that irrespective of the nature of the technology used, the responsibility for the valuation assignment continues to rest with the valuer.

IVS 104 – The Responsibility Cannot Be Delegated

One of the most important principles emerging from IVS 104 is that technology does not dilute professional accountability.

The standards specifically emphasize that:

Where a valuer uses AI and/or technology-based tools and resources employing opaque or non-transparent logic in the collection of data and inputs, the valuer remains ultimately responsible for IVS compliance.

This is a critical development for the profession because it clarifies that:

• reliance on software does not reduce liability,
• automated outputs cannot replace professional judgement,
• and technological sophistication is not a defence for inadequate diligence.

In other words, even if the valuation process is assisted by highly advanced AI systems, the valuer cannot merely accept the output at face value.

AI Now Influences Every Stage of a Valuation Engagement

The impact of AI is no longer limited to back-office calculations. Its use now spans almost every component of the valuation lifecycle, including:

1. Scope of Work

AI tools may assist in identifying engagement parameters, industry trends, and risk factors. However, the valuer must independently determine whether the scope appropriately addresses the purpose of the valuation.

2. Data and Inputs

Technology can rapidly collect market data, financial information, transactional benchmarks, and industry metrics. Yet the reliability, completeness, and appropriateness of those inputs must still be critically assessed by the valuer.

3. Valuation Models

Automated valuation models and AI-driven analytics may improve efficiency, but the valuer must evaluate:

• whether the methodology is suitable,
• whether assumptions are reasonable,
• and whether the outputs are consistent with market participant perspectives.

4. Documentation and Reporting

AI-assisted drafting tools can support report preparation, but the final report must still reflect:

• proper reasoning,
• adequate disclosures,
• transparency of assumptions,
• and compliance with applicable standards.

Professional Judgement and Scepticism Remain Central

The increasing use of AI actually makes the role of professional judgement even more important.

A valuer today must:

• question unusual outputs,
• validate assumptions independently,
• reconcile inconsistencies,
• understand the limitations of technology,
• and maintain professional scepticism throughout the assignment.

The profession cannot move toward a “copy-paste valuation” environment driven entirely by automated systems.

As rightly stated:

“Valuer is accountable, and professional judgement and professional scepticism remain at the core.”

This principle reinforces that valuation is not merely a computational exercise. It is an expert-driven professional opinion requiring analytical reasoning, contextual understanding, and ethical responsibility.

Greater Responsibility, Not Lesser Responsibility

Contrary to the perception that AI may simplify valuation responsibilities, the revised framework arguably imposes a more stringent obligation on valuers.

Today, valuers are expected to:

• understand the tools being used,
• assess their reliability,
• verify data integrity,
• evaluate algorithmic limitations,
• and ensure compliance at every stage of the engagement.

Whether dealing with business valuation, financial instruments, intangible assets, or other asset classes, the expectation is clear:
the valuer must maintain oversight from the commencement of the assignment until the final submission of the report.

Conclusion

AI is undoubtedly reshaping the future of valuation. It offers speed, scalability, analytical depth, and operational efficiency that can significantly enhance valuation practices. However, IVS 104 sends a strong and timely message to the profession:

Technology may assist the process, but it does not replace accountability.

The valuation conclusion remains the professional responsibility of the valuer. No algorithm, automated model, or opaque system can substitute the valuer’s duty to exercise professional judgement, scepticism, and independent verification.

As technology becomes more sophisticated, the role of the valuer does not diminish—it becomes even more critical.