Checklist for AI in Professional Services

As 2024 unfolds, the transformative impact of artificial intelligence (AI) on professional services is increasingly apparent. In a recent discussion on the Professional Services Pursuit podcast, hosted by Banoo Behboodi, Vecteris’ Eisha Armstrong explored how AI is helping professional services organizations rethink how they solve problems and create value.

Leaders in professional services are rightfully prioritizing AI, driven by compelling research that highlights B2B services as the sector most vulnerable to AI-driven disruption.

Eisha and Banoo discussed two major benefits of AI in professional services - transforming service delivery and innovating new offerings:

 

Transforming Service Delivery: AI should redefine—not just enhance—service delivery. Automating routine tasks like task handoffs and research creates significant capacity. An architecture firm told us about a new proprietary software acquired through a JV that can do 50% of the work an architectural engineer used to do. This opens the opportunity to do new things that change how organizations deliver services. For instance, firms might whitelist or develop proprietary AI tools for customer use or assist customers in harnessing existing AI technologies.

 

Innovating New Offerings: AI enables the creation of novel services and offerings. For example, an information services organization we work with cut human time spent on judgment-based data and information categorization by 95%, allowing investment in new bundled solutions that generate additional revenue streams. This approach not only diversifies service portfolios but also creates a competitive edge.

 

To transform service delivery and innovate new offerings, leaders should tie AI experiments and initiatives to specific objectives and plan for change management required for successful adoption. Starting with strategy is critical as the extent of organizational change flows from the organization's objectives.

 

Here’s a framework for the most common AI objectives we’ve seen from B2B professional services organizations. Vecteris then uses the change management checklist to assess key requirements to support the achievement of AI objectives. 

 

4 Objectives for AI in Professional Services

1. Automating Low-Value Tasks
  • AI automates repetitive tasks, such as writing code or conducting audits, improving speed and reducing costs.
  • Examples: Deloitte's DARTbot, Marsh & McLennan's LenAI.


2. Improving Knowledge Work Quality
  • AI frees up time for professionals to focus on complex analysis and client relationships.
  • Example: enhancing the quality of advice and recommendations with AI-augmented research and insights.


3. Optimizing Internal Workflows
  • AI streamlines internal processes by reducing meeting time and identifying business model weaknesses.
  • Example: automating handoff processes in service contract SLAs.


4. Creating New Growth Opportunities
  • AI enables firms to solve new client problems and develop innovative service offerings.
  • Example: Addressing an SMB or middle market segment with an AI-led offering leveraging a capability built for enterprise clients at a fraction of the cost. 

 

Checklist - 6 Elements of Change Management for AI
Vecteris uses this checklist in our coaching and advisory engagements to help organizations identify and prioritize key change management activities to support their objectives. The specifics will look different for each organization, but leaders should address each of these elements for any AI objective.

 

1. Workforce Transformation
  • Adapt roles and develop new skills to work with AI.
  • Encourage experimentation and quick learning.


2. Culture Change
  • Shift organizational values to prioritize learning, collaboration, and speed.
  • Move away from perfectionism and embrace experimentation.


3. Go-to-Market Changes
  • Reevaluate pricing strategies to reflect AI's impact on billable hours and service costs.
  • Focus on value-based pricing and the value delivered to clients.


4. Client Expectation Management
  • Communicate how AI affects deliverable quality, accuracy, and data security.
  • Ensure clients understand the value AI brings to services.


5. Co-Design and Co-Development
  • Collaborate with clients to understand their needs and how AI can address them.
  • Develop new solutions based on client feedback and requirements.


6. Performance Measures and Rewards
  • Shift focus from billable hours to project margins and value creation.
  • Reward behaviors that align with AI adoption, such as learning, collaboration, and innovation.

 

How Vecteris Can Help

Vecteris’ Productize Pathway® Solution enables companies to develop and commercialize productized offerings quickly and cost-effectively.

Contact us to learn how we can help you confidently implement AI in your service and product offerings!