How AI is transforming consulting: Opportunities and challenges for clients

In the rapidly evolving landscape of financial services, the Netherlands is on the eve of a transformation in which artificial intelligence (AI) plays a central role. Financial institutions are facing complex challenges that require innovative solutions. AI consulting is evolving from a support service to a strategic necessity, with the integration of advanced technologies fundamentally changing how advisory processes are carried out.

This article highlights how AI is transforming the consulting industry and what opportunities and challenges this presents for clients, with a particular focus on the Dutch financial sector.

Strategic advice: The power of AI-driven decision-making

The strategic advisory practice is undergoing a revolution with the integration of AI technologies that accelerate scenario analysis and enable data-driven decision-making. Financial institutions face the challenge of adapting their business strategies to a rapidly changing market, with AI playing a crucial role in modeling future scenarios.

The added value of AI in strategic consulting lies mainly in:

• Accelerated scenario analysis: AI tools can calculate thousands of scenarios in minutes that would previously take days or weeks, allowing banks and insurers to respond more quickly to changing market conditions.
• Data-driven strategic decision-making: By combining various data sources, AI systems can identify patterns that remain invisible to human analysts, leading to more informed strategic decisions.

Implementation projects: RPA and AI for process automation

In addition to strategic advice, AI is also transforming implementation-oriented consulting, with Robotic Process Automation (RPA) combined with AI increasingly being used to optimize operational processes. In the Dutch financial sector, we are seeing increasing adoption of these technologies to automate compliance processes, administrative tasks and customer communications.

Concrete applications in the Dutch context are:

• Automation of compliance checks: AI systems scan transactions and documentation for regulatory deviations, which is particularly relevant given the stringent compliance requirements in the financial sector.
• Process optimization: RPA solutions automate document and data processing, which reduces error rates and increases efficiency.
• Customer communications: AI-driven communication systems personalize customer information, such as ING Belgium’s virtual assistant “Ida,” which processes more than 70% of customer requests without human intervention.

However, a key risk in these implementations is the over-reliance on AI models without adequate human validation. Research shows that only a quarter of Dutch people are optimistic about the use of AI by financial institutions, underscoring the importance of human verification.

💡 Opportunities: Efficiency, transparency and predictive capability

The integration of AI into consulting services offers clients in the financial sector significant benefits:

• Cost reduction through more efficient processes: AI tools analyze RFPs (Request for Proposals) up to 70% faster than traditional methods, leading to significant time and cost savings in the procurement phase of consulting projects.
• Real-time dashboards for transparency: AI-powered dashboards provide clients with continuous insight into the progress and results of consulting projects, increasing transparency and enabling adjustments.
• Predictive analytics for risk management: Advanced AI models identify potential risks at an early stage, which is particularly valuable for financial institutions.

Dutch financial institutions that have implemented AI report operational cost savings of up to 30-40% and a significant improvement in the quality of decision making.

⚠️ Pitfalls: Standardization, ethical dilemmas and cybersecurity

Against these benefits, however, there are also substantial risks that require careful attention:

• Excessive standardization of consulting: AI systems tend toward standard solutions based on historical data, which can lead to a lack of customization and innovation in consulting advice.
• Ethical dilemmas in algorithmic decision-making: AI models may contain unintended biases that lead to unfair or discriminatory outcomes, a risk particularly relevant in the financial sector.
• Cybersecurity risks with sensitive data: The large-scale processing of personal financial data by AI systems increases the attack surface for cybercriminals, which requires specific security measures.

For Dutch clients considering AI-driven consulting services, careful partner selection is essential. The following checklist provides guidance for this decision:

Does the party have a clear AI governance framework?

A robust AI governance framework is crucial to ensure ethical, transparent and compliant AI practices. Clients should verify that potential consulting partners have:

• Clearly defined roles and responsibilities for AI oversight
• Procedures for identifying and mitigating bias in AI models
• Compliance mechanisms consistent with Dutch and European regulations, including the EU AI Act

How is explainability of AI decisions ensured?

Explainable AI (XAI) is essential to building trust and complying with regulations. Clients must verify that consultants:

• Using transparent AI models whose decision making is traceable
• Have methodologies to make complex AI decisions understandable to non-technical stakeholders
• Conduct regular model reviews to ensure the quality and reliability of AI outputs

Is there a hybrid human-AI workflow?

The most effective AI implementations combine technological capabilities with human expertise. Clients should evaluate whether consultants:

• Taking a balanced approach where AI automates repetitive tasks while human experts focus on strategic decision-making
• Engage senior experts in the interpretation and validation of AI-generated insights
• Have clear protocols for situations where human intervention is necessary

The transformation of consulting services starts as early as the sales phase, where AI is revolutionizing traditional RFP processes. An illustrative case study from the Dutch financial sector shows how a mid-sized bank realized 70% time savings by implementing AI-driven RFP analysis.

This bank implemented an AI solution that included three core components:

1. Natural Language (NLP) for parsing complex issues: Natural Language Processing algorithms analyzed RFP documents in minutes instead of days.
2. Dynamic pricing models based on historical quotation data: AI systems analyzed historical quotation data to generate optimal pricing models.
3. Automated content generation: Based on a centralized knowledge base, the AI system generated initial content for proposals.

The transformation of AI consulting offers Dutch financial institutions unprecedented opportunities to address complex challenges more efficiently and effectively. At the same time, implementing these technologies requires a careful balancing of risks and benefits.

For clients considering AI-driven consulting services, the following actionable tips are essential for risk mitigation:

1. Implement a phased approach: Start with small-scale AI pilots before moving to large-scale implementation so that risks remain manageable.
2. Invest in AI literacy: Make sure your organization has sufficient knowledge to critically evaluate AI recommendations.
3. Demand transparency and explainability: Do not accept “black box” solutions, but insist on transparent AI models.
4. Develop a robust governance framework: Define clear responsibilities, ethical guidelines and control mechanisms for AI implementations.
5. Adopt a hybrid approach: Combine AI capabilities with human expertise to leverage the benefits of both worlds.

With the right approach, AI consulting can be a powerful catalyst for innovation and efficiency in the Dutch financial sector while effectively managing risk. The key to success lies in a balanced approach that combines technological advances with human insight and ethical considerations.

Stephan Linnenbank is consultant and  supervisory board member