AI and the Future of CLM

Dirty Data Kills!

Bad data is responsible for over 70% of unsuccessful billing software implementations. Erroneous data also has profound implications for crucial processes like CPQ, CRM, revenue recognition, financial reporting, analysis, and forecasting. Our latest research note sheds light on the scope of the data hygiene problem.

MGI estimates that a 0.1% error rate caused by dirty data within financial and CRM systems translates to at least 1% revenue leakage. Without a clear focus on continuous data management, companies with dirty data have perennial problems with information integrity, billing disputes, and revenue leakage – among other issues.

We identify three factors that are primarily responsible for quote-to-cash and billing data problems:

1. Lack of proper scope

2. Rate of change

3. Lack of focus on data

Between the lines | The scope of the billing data challenge goes much deeper than just the volume of data or its cleanliness – that’s why deploying ETL (“Extract-Transform-Load”) or MDM (“Master Data Management”) tools aren’t sufficient answers to the data hygiene problem. Data cleanup should be viewed as a continuous process, not as a one-time phase to be completed.

Why you should care | The full report delves into nine key dimensions that are critical to understanding the scope of the billing data challenge and outlines a roadmap for businesses to navigate the complexities of data hygiene, supply and distribution, and rapidly growing data volumes.

Get the report here.

AI and the Future of CLM

If you missed our webinar on AI and the Future of CLM, you can watch it on our site here.

MGI analysts sat down with Grant Peterson, CPO of Conga and the former CTO of DocuSign, to discuss his thoughts on AI’s potential to transform the CLM landscape.

Here are a few quotes to summarize the key takeaways from our conversation with Grant:

• “I don’t think we’re ready to let software practice law.” The correct role for Gen AI (within CLM) is to ideate and help provide perspective for licensed attorneys, not authoring contracts by itself.“
• Every single vendor in every single industry you’re in, including CLM, is going to have the exact same set of generative capabilities, because none of us are building them. We’re buying them.” With that in mind, is Gen AI truly capable of providing differentiation, as the market has been led to believe?
• “If the industry’s ready for a pretty significant hike in the floor of the price, this could be table stakes.” But Grant doesn’t think the industry is quite ready for that.
• Gen AI and more traditional machine learning could go hand in hand. Running data through Gen AI first, then through ML models, yields better results than just using Gen AI, and quicker results than just using ML.
• It’s likely that AI could allow implementation times to get cut in half within the next 12-36 months.
• Finally, three key issues Grant has been thinking about are:
  • How do you create real value with Gen AI, rather than great marketing?
  • How can you do that in a way that protects customers’ confidentiality?
  • What does Gen AI make possible that is actually new?

Zoom out | If we had to summarize this entire 45-minute conversation into one piece of advice, it would be this: try everything, trust nothing.

For more insights from this illuminating conversation, watch the webinar on-demand now.

How Are C-suites Approaching the Gen AI Opportunity Today?

MGI Research is currently conducting a survey to find out how CEOs and other C-suite execs are approaching the Gen AI opportunity. We will publish a more in-depth analysis of our findings in an upcoming issue of The Margin, but in the meantime, here’s a sneak peek at what we’ve learned:

• So far, all respondents say they view AI as a major opportunity in their industry – but not an existential threat.
• However, those same respondents are mixed on whether AI actually affects their TAM at present, as well as how they predict it will affect their business margins in the near future.
• Some respondents report that AI is already a factor for customers in deals, but so far no one believes it is the primary driving factor.

Early insights | Our favorite quote from the survey responses so far:

“[AI] needs to be approached with pragmatism as the framework, along with a recognition that AI is always used in a ‘human centric’ context as an enabler rather than an elixir.”

It’s not too late | This is a reminder to any C-suite execs who have received our invitation to participate in the survey: don’t forget to fill it out this week!

• It only takes 2 minutes to complete, and participants will receive a free copy of our findings.
• If you are a C-level executive who wants to contribute your thoughts on the impact of AI in your industry, you can reach us here.

The Usage Pricing Revolution

MGI analysts Andrew Dailey and Igor Stenmark will join BluLogix CEO Youssef Yaghmour next week to discuss how organizations can achieve success with consumption pricing.

Join the webinar to learn about best practices for implementing a successful, data-dependent usage billing project that fuels continuous, real-time processing, including managing changes in customer accounts, usage patterns, contracts, or purchase history, and ensuring that they are accurately and promptly reflected in up-to-date statements, invoices, and order execution to drive business growth.

The BluLogix webinar will take place on Wednesday, November 15 at 11am PT / 2pm ET. Register now to reserve your spot!