If you’ve ever felt like your sales and services teams are working overtime to keep customers from getting lost in a maze of complexity, you’re not alone. Across industries, businesses are pouring more resources than ever into sales and services labor—not to drive growth—but to shield customers from overly complicated journeys.

The root of the issue? A B2B customer lifecycle that’s no longer fit for purpose in today’s fast-paced, outcome-driven environment. The good news? AI is emerging as a powerful tool to simplify these processes, reduce inefficiencies, and refocus your teams on delivering real value.

In this blog, we’ll explore why traditional customer lifecycles are falling short, the key challenges businesses like yours face, and how AI is positioned to drive the transformation you need. Whether you’re navigating this shift now or planning for the future, you’ll find insights and actionable takeaways to guide your strategy.

Let’s dive in.

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How AI Can Drive Revenue Growth—If You Overcome These Common Roadblocks

AI is already revolutionizing support and education services, streamlining workflows, resolving customer issues faster, and improving overall service efficiency. However, many companies still struggle to unlock AI’s full potential in revenue-generating functions, like sales and marketing.

So, what’s standing in the way? Research points to three common barriers:

• Weak sales and customer data: AI tools can’t deliver reliable insights or recommendations without accurate, well-organized data.
• Limited investment in research and development: Sales and marketing often lag behind other departments regarding AI-focused innovation and experimentation.
• The “vision problem”: Leadership priorities don’t always align with where customers see the most value, creating a disconnect that stifles AI adoption.

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Despite these challenges, some companies have seen significant success with AI in their sales and marketing efforts. By improving data quality, aligning leadership goals with customer needs, and committing to ongoing AI investment, they’re turning potential roadblocks into opportunities for growth. These success stories offer valuable lessons and a practical roadmap for businesses like yours, ready to harness AI for measurable revenue impact.

Related: AI Use Cases for Generating Revenue

Using Customer Success as 'Customer Zero' To Refine AI Capabilities

When rolling out new AI technologies, one of the most effective strategies might already be within your organization: leveraging your customer success team as “Customer Zero.”

Microsoft’s Mike Flannagan shared how the company's customer success organization became the testing ground for its new co-pilot AI technology. By beta-testing these capabilities with its engineers and support agents, it gathered feedback, refined workflows, and ensured the product was ready for a more significant launch. This internal testing smoothed the rollout and helped identify real-world challenges before it reached paying customers.

But rolling out AI isn’t just about having the right tools—it’s about ensuring adoption across your teams. Flannagan highlighted a key challenge: while their support teams quickly embraced AI tools, their sales teams lagged.

So, where should you start?

• Integrate AI into existing workflows: Instead of introducing entirely new systems, embed AI tools into your teams' daily processes.
• Focus on role evolution: Understand where roles might need to shift or evolve to fully leverage AI’s potential.

AI will likely drive a new level of process and data-driven thinking in sales—something we haven’t seen before. But for this transformation to take hold, organizations like yours must approach AI adoption not just as a technology rollout, but as a shift in how teams think, work, and deliver value.

Related: Put AI To Work for Customer Success

How To Get Your Employees Invested in AI Adoption

Introducing AI into your organization isn’t just about choosing the right tools and ensuring your teams use them. How do you get employees to adopt AI and genuinely care about its impact?

Jessica Kriegel of Culture Partners tackled this question head-on, offering a clear framework for securing employee buy-in amid the uncertainty, often accompanying technological change.

At the core of her approach is a focus on employee fulfillment. When teams understand why AI matters—not just to the company, but to their roles and success—they’re far more likely to embrace it.

Here are some key principles to consider:

• Communicate the 'why': Clarify how AI adoption aligns with your company’s mission and employees' responsibilities.
• Address fears and misconceptions: Many employees worry that AI will replace rather than empower them. Transparent conversations can ease these fears.
• Celebrate early wins: Highlight quick successes to demonstrate AI’s value and build momentum.

As Kriegel emphasized, successful AI adoption requires more than training sessions or top-down mandates—it demands a cultural shift. You'll see real engagement and impact when your employees see AI as a tool that enhances their capabilities rather than threaten their roles.

Related: The Hard Truth About Mastering Change Management

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Where To Invest for Maximum Impact on Customer Success

Regarding customer success, one question looms large: How much should you invest to see meaningful results? According to Abbas Haider Ali, VP of Customer Success at GitHub, the answer is clear: companies should aim to allocate 10% of their revenue to customer success functions.

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However, simply setting aside a budget isn’t enough. To maximize your return on investment, you need to know where to focus those resources.

Key areas highlighted by Haider Ali include:

• Customer Success Management (CSM): Equip your team with the tools, training, and resources they need to build strong customer relationships and drive value realization.
• Renewals: Proactively manage renewals to reduce churn and ensure customers continue to see value in your product or service.
• Professional Services: Invest in services that help customers achieve faster, more tangible outcomes.
• Support: Strengthen your support infrastructure to resolve issues quickly and effectively to boost customer satisfaction and trust.

The goal isn’t just to spend on customer success—it’s to spend smartly. Every dollar should contribute to building stronger customer relationships, reducing churn, and driving long-term growth.

Making the Shift From On-Premise to As-a-Service: Overcoming Key Roadblocks

Transitioning from traditional on-premise hardware solutions to an as-a-service model isn’t just a technical shift—it’s a cultural and operational transformation. Many companies are progressing, but few feel confident enough to make their efforts a success.

Philips Healthcare stands out as an exception, and their success stems from a clear understanding: their challenges mirror what their customers are experiencing. By addressing these shared obstacles, Philips was able to align their internal teams, gain buy-in, and create tangible value for their customers.

But this transition isn’t without roadblocks. Two significant challenges often cause hesitation among customers:

• Shifting to a proactive mindset: Customers accustomed to reactive support often struggle to see the value in proactive, always-on service models. Bridging this gap requires clear communication and tangible proof of the long-term benefits.
• Implementing advanced telemetry: Hardware solutions must evolve to include more intelligent, advanced telemetry systems capable of monitoring performance in real-time and predicting issues before they occur.

These aren’t just technical hurdles—they’re mindset shifts for your internal teams and customers. Companies that invest in education, transparent communication, and advanced technology infrastructure, are better positioned to navigate these roadblocks and deliver lasting value.

Scaling With AI and Delivering Real Value

As businesses face mounting pressure to scale operations, reduce costs, and drive revenue, one thing is clear: AI will play a central role in shaping the future of customer success.

For many organizations, the question isn’t whether to adopt AI—it’s how to do it effectively. The answer lies in balancing innovation with clear, measurable customer value.

While the road to AI maturity may seem complex, one thing is sure: companies that successfully align their sales, customer success, and AI strategies will be best positioned to scale effectively and deliver sustained value to their customers.

Your Key Takeaways

• Aligning sales and customer success teams: This strengthens a partnership between these functions, ensuring smoother handoffs, better communication, and a more seamless customer experience.
• Starting small with AI adoption: Instead of attempting an organization-wide overhaul, identify specific workflows or pain points where AI can deliver quick, visible wins.‍
• Focusing on customer value: The customer experience should remain the north star of your AI adoption strategy at every stage.