Artificial intelligence (AI) has been around for decades, but only recently has it begun revolutionizing industries across the globe, and the professional services space is no exception. Regular media coverage, increasing public interest, and incredible competition has resulted in a surge in AI hype. For professional services firms seeking a competitive edge, the successful integration of AI has become imperative. This article explores from a “boots on the ground approach” what works, what doesn’t, and how organizations can build a foundation for success.
The Importance of AI in Professional Services
AI will likely transform professional services by enabling content creation based on internal data and providing the ability to quickly query large data sets and automate routine tasks. It also can enhance decision-making and provide valuable insights while dramatically increasing efficiencies within the business. The expectation therefore is that professional services firms that “embrace AI” will improve efficiency, reduce costs, and deliver better client outcomes.
However, the journey to successful AI integration is not a smooth and easy one and requires careful planning and execution to avoid costly mistakes, such as the inability to identify and pilot test strong use cases, and AI disillusionment.[1]
The First Steps
Use What Comes Out of the Box First: It’s tough to hear but it’s best for organizations to start with what is available in an “off the shelf tool” such as Microsoft Copilot. Begin by mastering the tools provided by the AI platform before exploring additional features. Competition makes certain that AI providers will regularly offer updates and new models; ensuring proficiency in the basics will set the foundation for future advancements.
Clear Strategy and Vision: A well-defined AI strategy and implementation plan[2] is crucial. Firms must identify key areas and their unique business pain points and consider where AI can add value. Also important, and perhaps most difficult of all, is the need to set realistic expectations. This involves understanding the specific needs of the business in painstaking detail and taking care to align AI initiatives with the organization’s overall goals.
Leadership Buy-In: Strong support from leadership at all levels is essential for AI success. Leaders play a pivotal role in championing AI projects and fostering a culture of innovation. Their commitment can drive the adoption and success of AI across the organization.
Cross-Functional Collaboration: Perhaps most key is that AI projects thrive on collaboration across departments—silos be gone! By integrating AI solutions into existing workflows and sharing successes internally, firms can ensure seamless implementation and maximize the benefits of AI.
Pilot Projects: Starting with pilot projects allows firms to test AI solutions on a smaller scale. Identify repetitive processes and pain points, and consider: What could be accomplished if these processes were handled by an AI agent? Those small wins matter, and practical, nonflashy projects can still bring that wow factor. Also important is gathering feedback on these small pilot projects. This will enable the organization to develop metrics that will help it understand what works—and what does not.
Be Clear About What Doesn’t Work for You
Lack of Clear Objectives: AI projects without clear objectives and measurable outcomes are likely to fail. Defining success from the outset is crucial to guide the project and evaluate its impact.
Underestimating Data Quality: AI relies heavily on an organization’s data. Poor data quality or forcing data to fit a use case can lead to inaccurate insights and predictions. Firms must prioritize data governance and quality control to ensure reliable results.
Ignoring Change Management: Make no mistake, implementing AI will disrupt existing processes and roles. Addressing change management and providing education and training is essential to ensuring smooth adoption and minimizing resistance.
Overlooking Governance, Security, or Ethical Considerations: AI ethics and governance are critical. Firms must consider the risks and ethical implications of AI use and establish guidelines to ensure responsible AI deployment.
So How Can Organizations Build a Foundation for Success?
Invest in Talent: Investing in AI talent will be key.[3] Firms should hire data engineers, data scientists, AI engineers, and domain experts. Perhaps most importantly, however, firms will need to identify business-side champions who understand the work and AI’s potential. Firms will also need to re-evaluate the continuous learning and development programs that have been in place for decades to ensure they can help keep the team updated with the latest AI advancements.
Outside Help: Nobody knows the business better than members of your organizations, but consider: Do current practice leaders have that impartial viewpoint, that cold-eyed view on whether that AI project should be a “go” or “no go”? Firms would be wise to consider engaging an external AI subject-matter expert who is able to be objective while working to take the organization to the next level.[4]
What’s Next?
Robust Infrastructure: A scalable and secure AI infrastructure is vital. This includes the organization’s cloud service provider, such as Azure or AWS; data storage solutions such as Azure Blob storage; and an AI platform(s) that aligns with your firm’s AI initiatives.
Organizations should consider the following questions:
- How can the organization scale AI responsibly?
- Who owns the roadmap?
- What does AI fluency look like across the organization’s nontechnical teams?
The Bottom Line
To be successful, AI implementation doesn’t have to be perfect—the organization just needs to stay the course. AI in professional services isn’t about replacing what the organization does; it’s about working smarter, faster, and more focused. And that starts with showing up, learning, and being open to what’s possible.
[1] Gartner Inc., “Explore Beyond GenAI on the 2024 Hype Cycle for Artificial Intelligence” (accessed 15 April 2025), https://www.gartner.com/en/articles/hype-cycle-for-artificial-intelligence.
[2] Microsoft, “Deploying Microsoft 365 Copilot in Four Chapters,” Inside Track (accessed 15 April 2025), https://www.microsoft.com/insidetrack/blog/deploying-copilot-for-microsoft-365-in-four-chapters/#chapter-2.
[3] Keith Ferazzi, “Talent Reimagined: How AI Will Elevate Human Potential,” Forbes, 1 April 2025, https://www.forbes.com/sites/keithferrazzi/2025/04/01/talent-reimagined-how-ai-will-elevate-human-potential/.
[4] Matthew Mottola, “Why Your AI Strategy Will Fail Without the Right Talent in Place,” Entrepreneur, 11 December 2024, https://www.entrepreneur.com/leadership/why-your-ai-strategy-will-fail-without-the-right-talent-in/483572.