February 8, 2025
Three things service businesses need to know about AI now

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Scott Brown is the President and CEO of certinia (formerly Financialforce).

This photo Took a tour over the last month and got more than a few smiles. However, behind the momentary exuberance lies a harsh business reality: AI is everywhere, and there’s no such thing as a business person who isn’t thinking about it.

How reliable is propaganda? How relevant is AI to you as a services business leader? From flag waving to handshakes, there’s certainly no shortage of AI content. So it can be challenging to know whom to consult on your business’s approach to AI.

At Certinia, we regularly engage in open dialogue with our clients about how AI can play a role in their business strategy. I’d like to share some learnings from these conversations. Here are three key points that we are applying to our business. Perhaps you can apply these to yourself.

1. It’s all about the data

The famous British mathematician Charles Babbage said, “The errors made using insufficient data are much smaller than those made using no data at all.” He was ahead of his time. For any AI tool to be successful, the cleanliness and ongoing sanitization of data is critical.

The issue is compounded when business data is used to decide which deals to pursue, where to hire or upskill, or when to initiate a collection process to manage cash flow. Go If you have incorrect test data from long-deployed PSAs, and/or duplicate sales opportunities in your CRM, the “real” picture of what has happened and is happening in your business will be skewed.

Before deploying any AI tool, make sure you have a complete understanding of your business data, where it is stored and how clean it is. If you’re looking to invest in an enterprise-grade tool to streamline your services business, consider this data sanitization in the merits. Here’s a handy two-item checklist:

  • Trust the security of data storage and its ability to easily report on all data. (Collecting data from many sources using different systems can be costly.)
  • Develop clear ways of storing and deleting unwanted data. (Good partners in the AI ​​field can give you advice here.)

2. Start with the use case, not the technology

One thing AI has in common with other technologies: The technology itself should not drive your decision making. It’s easy to be enticed by shiny new items when you move with the technology rather than the use case. Furthermore, deploying complex tools to solve a problem can often make your technology more complex – so complex, in fact, that the ROI on some AI tools can be difficult to understand.

Instead of leading with the technology, lead with the problem you’re trying to solve. Then back to the technology that helps solve that problem. Inverting the narrative this way, it comes down to “How can my business use GPT or natural language processing or other AI tools to increase productivity?” and “What tools will help me solve X business problem?”

Closed-loop use cases are key here – namely, which AI tools will close the loop to make insights actionable and challenges solvable? For example, instead of recommending corrections to the job description to improve margins and take into account risk, create a mechanism to display and accept changes and send them to the customer. loop closed.

3. Focus on upgrade, not replacement

Will AI replace your employees? Will it replace you? This is a real concern that should not be dismissed. When China-based video game company NetDragon Websoft announced in March that it had replaced its CEO with an AI backend, the company actually saw its stock price jump. It’s a little troubling for any high-ranking executive.

My own belief is that AI will not replace knowledge workers. Rather, it will assist them in doing their work in an optimized and efficient manner. We are already seeing the market recognize and embrace this human/machine hybrid model. Consider that today’s AI product names (Co-Pilot, Genie, etc.) indicate that they require a human to complete the task they are designed to streamline or automate.

In fact it is an inflection point. Business leaders have the opportunity to work closely with their employees to address the following questions:

  • What parts of each employee’s role have the most impact?
  • What added value could they bring to the business if they had more time?
  • What makes them happy at work?

In our company’s recent survey of 900 consultants and consulting managers in the US, most said they want to use their skills to solve tough problems and make a greater impact. AI can be a powerful tool in achieving that goal. For that reason, we should re-name “AI concern” as “AI opportunity” – a chance to achieve personal growth and professional impact. Roles will definitely change. But it may be for the better. Be open and transparent in your communication with your employees and together you will be able to determine future roles.

final food for thought

No matter where your service business is in its digital transformation journey, you should play an active role in collaborating on AI readiness. Be honest with yourself in answering questions about your company’s data preparation (eg, where is it? Is it secure? Is it clean?).

AI probably won’t replace you. But if a competitor is taking advantage of better AI than you, then maybe. Work with vendors to shape the AI ​​tools of the future that solve real problems today. Leverage your network of peers and colleagues to learn, collaborate and share AI knowledge and use cases. And openly and transparently leverage the skills and expertise of your HR business partners and your own employees as these new technologies emerge.


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