Overview
For middle market companies that operate lean and value adaptability, artificial intelligence is arguably the most alluring and provocative emerging technology for unlocking productivity, improving outcomes, saving time and money, and gaining or keeping a competitive edge. Yet, for many leaders, it is difficult to know exactly how to harness the potential power of AI and where to put it to work in the business. According to Middle Market Indictor data, most middle market companies—58%—remain in the early phases of AI adoption, either learning or discovering more about the technology or just beginning to try it out. While more than a quarter of businesses (29%) are already using AI to meet business needs, just 14% of companies say AI is fully embedded in the business. Clearly, most middle market companies have much further to go in their AI journeys. However, resource, budget and time constraints— the very issues AI promises to help resolve—are the primary hurdles to investing more in AI.
In this case study, we take an in-depth look at how a middle market technology consulting firm leveraged its own AI transformation as a launchpad to guide its clients’ experience. By embracing AI through the strategic integration of Microsoft Copilot, the company not only increased internal productivity but also developed a roadmap it now uses to help clients successfully invest in and navigate their own AI adoption journeys.
The Opportunity
Master the next it inflection point to drive value internally and for clients.
As business consultants and technologists with a proven knack for spotting the next big thing, the Weidenhammer team was quick to recognize generative AI tools as the game changers they are, especially for lean organizations. Weidenhammer operates in the unique position of both being a middle market company and serving other middle market businesses. The leadership team intuitively understood the value of AI— especially AI capabilities embedded into the tools its team already used every day—to reduce repetitive work, improve workflows, and increase internal productivity for itself and its clients.
By capitalizing on the opportunity to test generative AI capabilities ahead of the curve, Weidenhammer knew it could improve its own productivity while gaining the expertise to confidently guide other organizations, leveraging lessons from its own experiences to drive tangible value for the businesses it serves.
What drives us is looking for opportunities where technology can be a paradigm shift and catalyst for growth in our clients.
— Charles Zwicker, Weidenhammer President and COO
The Approach
Adopt a familiar platform, scale success through use cases and internal champions, and turn time saves into tangible value.
Weidenhammer took a pragmatic and deliberate approach to its AI rollout, beginning on familiar ground with the AI capabilities already integrated with the Office 365 tools in daily use across the company. Weidenhammer—and now, its many middle market consulting clients—build AI success on the following four key pillars.
1. Start with the right product
With any transformative technology, embedding new capabilities into familiar environments is a smart way to smooth the transition and make the learning curve a little less steep. This is exactly what Weidenhammer elected to do with AI, choosing to focus on existing Microsoft Copilot capabilities within Microsoft 365 applications, including Outlook, Word, Excel, PowerPoint and Teams. Looking beyond its own adoption toward future client work, Weidenhammer leadership knew it would gain expertise it could later apply to other Copilot tools for code generation, QA and testing to expedite its client projects.
Further, Weidenhammer knew it would be relatively easy to help its clients follow a similar approach with their own AI adoption journeys, as so many solutions, from accounting packages to collaboration software, already have AI baked into them. Ultimately, by leveraging existing AI capabilities to support its existing workflows, Weidenhammer checked the first box for its AI rollout by assuring its technical readiness: It already had the infrastructure, governance and security in place for the transition ahead.
2. Engage early adopters
As seasoned consultants, Weidenhammer knows all too well that technical readiness is just one part of the equation when it comes to successfully integrating new technologies. Cultural readiness is equally critical and usually represents the bigger stumbling block in adoption journeys. Fortunately, all companies have early adopters they can tap to help champion the cultural evolution that needs to occur before an organization can realize the upside of new technologies.
“Your early adopters are the ones who are going to understand where technology can drive improvements in your particular business. They understand how the business works. They also understand where the bottlenecks are, where process improvement and the automation of repetitive tasks can drive acceleration in your organization,” says Zwicker.
By engaging and empowering the roles most suited to benefit from the technology—early adopters like sales, marketing, developers and client engagement managers—Weidenhammer built a team of internal ambassadors for Copilot adoption. The early adopters logged quick wins with the AI tools, and then they eagerly helped evangelize adoption organically across the company by sharing their successes and pitching in to inspire and educate their peers.
3. Define use cases
While early adopters rarely need much convincing to give new technologies a try, to gain critical mass within an organization, most people need a compelling reason to explore doing their work in a new way. In middle market companies, which typically run lean, the opportunity to drive efficiencies can be a powerful motivator.
Weidenhammer used traditional business process re-engineering to identify bottlenecks in workflows and manual processes ripe for automation. Tasks such as transcribing and summarizing meetings, drafting emails, writing and testing code, creating client-facing materials, and answering frequently asked HR questions all became initial use cases for Copilot.
From there, company leadership encouraged its people to think of AI as an assistant that could help expedite routine tasks or contribute to solving problems or issues in their daily work. This mindset helped the Weidenhammer team view AI not as a threat to their jobs but as a powerful aide to help save time and make people more efficient and productive.
4. Foster a culture of experimentation and knowledge sharing
The Weidenhammer leadership team was very intentional about encouraging AI adoption in an unstructured way at first. Allowing people to play with the technology and see what it could do was an important first step in creating a comfort level. As the organization began to gain momentum with Copilot, it introduced structure around the adoption journey by establishing role-based teams to collaborate on defining, documenting, and sharing current and new use cases for both internal and client purposes.
As part of the learning process, Weidenhammer encourages associates to take full advantage of the free training resources available from Microsoft and to actively explore how other organizations use the tool. This hands-on, curiosity-driven approach has been key to accelerating adoption, as team members quickly became excited about discovering new use cases and expanding the possibilities of what AI can do.
All learnings gained through this experimentation are informing the company’s sustainable AI strategy and will help guide Weidenhammer toward the AI tools it will adopt and implement next. Weidenhammer teams are keeping an especially close eye on emerging AI technologies in the code development space and will leverage their experiences with Copilot to ensure success with additional AI tools in the future.
5. Optimize the time savings
Across departments, the Weidenhammer team has realized significant time savings through the implementation of Microsoft Copilot. According to Zwicker, the number of hours saved is not nearly as important as how those extra hours are utilized. To realize the greatest ROI on investment in AI, all Weidenhammer associates are expected to consider how they can use the time to maximize the value they bring to the organization and/or to the clients they serve. Appropriately repurposing time is where the true value of AI lies.
Zwicker notes that, for many organizations, a potentially unexpected outcome of AI will be the need to rethink how services are billed, especially for professional services firms using pricing models based on associates’ time and hours worked. Faster work doesn’t mean less value. Conversely, speed offers additional benefits in terms of time to market and outpacing the competition. Companies will need to make the shift from time-based to value-based pricing as they become more proficient at using AI to enhance the productivity of their teams and improvements to their client offerings.
AI has certainly created more productivity and time savings. But what I didn’t expect was once we got past that learning curve and we kind of hit critical mass, now I’ve got people saying we need to use AI for this and this and this. The ability for them to ideate around how AI can help our clients and help ourselves was something that I didn’t expect as quickly as it materialized.
— Charles Zwicker, Weidenhammer President and COO
The Results
An organization empowered to deliver greater value
At Weidenhammer, adopting AI hasn’t just automated tasks; it has elevated employee capabilities, driving increased creativity and problem-solving acumen. Copilot has become a personal assistant for executives, developers, marketers, consultants and other team members, freeing Weidenhammer associates to do more of their most valuable work every day. Even more importantly, the adoption journey has created a culture of ideation that will allow the organization to continue to improve through additional strategic AI adoptions. By viewing AI as the enabler it is meant to be, team members are proactively looking at existing and new technologies as catalysts to meeting organizational and client needs faster and more effectively than ever before.
30%
Time savings on routine tasks such as documentation, email drafting and project planning
20%
Increase in productivity through the automation of repetitive work and enabling employees to focus on strategic tasks
25%
Faster development cycles for client projects, resulting in quicker time to market