AI has become one of the most talked-about topics within go-to-market (GTM) teams as they aim to move faster, scale smarter, and deliver more with fewer resources. No longer a futuristic concept, AI is a present-day reality that comes with alluring benefits across four key areas of GTM operations:

  1. Supporting scaling: Manual processes may work for small teams, but they break down as complexity and volume grow. With AI capabilities, scaling can be successful without relying on increasing headcount.
  2. Automating repetitive tasks: Time-consuming activities such as data entry, dynamic customer segmentation, and data normalization can all be taken over by AI, freeing up teams to focus on higher-value work.
  3. Refining workflows: AI can analyze where processes fall short, then recommend improvements that ultimately help teams streamline their work.
  4. Reducing human error: AI helps validate data, monitor workflows, and maintain consistency, leading to better performance and fewer costly mistakes.

With these benefits, it’s tempting to want to rush into AI adoption. Regardless of the potential, however, the hard truth is that you’ll never unlock AI’s benefits when your foundation is broken. AI doesn’t independently repair inefficiencies. It accelerates whatever’s already in place, whether that’s a well-oiled workflow or a disjointed one. That’s why it’s essential to take a hard look at your current state from which you’re building before adopting automation. For GTM teams, focus on areas such as:

  • Addressing siloed processes. Teams struggle to enhance customers’ experiences when cross-functional process requirements are not well understood, roles and responsibilities are unclear, or SLAs are not in place. To overcome this, organizations should look at their processes end to end, regardless of team or function, and visualize the sequencing and intersection of processes to ensure alignment across the go-to-market ecosystem.
  • Integrating technologies. When systems are disconnected, automation breaks down — slowing productivity and increasing errors. GTM teams must understand their data and workflow needs to determine which technologies need to be integrated to enable continuous data flow and automation.
  • Data inconsistencies. Fragmented, inaccessible data leads to inaccuracies, redundant work, and biased outputs that undermine decision-making. To address this, organizations should build a strong data governance foundation to make data consistent, discoverable, and trusted across teams.
  • Intentionally managing change. Even the best processes and tools fail if teams aren’t equipped, or willing, to adopt them. To succeed, organizations should employ change management best practices, communicate clearly about automation plans, actively seek employee input on technologies that impact their work, and ensure that strong training and enablement is in place.

Improving efficiency isn’t just a good idea; it’s already a priority for your competitors. In Forrester’s Priorities Survey, 2024, 41% of global B2B business and technology professionals with a revenue growth priority plan to drive growth by optimizing efficiency. Focusing on your foundation together with AI deployment is a great way to gain the efficiency and growth you’re looking for.

Forrester can help GTM teams optimize processes, data, and technologies and identify areas where AI will expedite goal achievement. Clients can read my report, Unlocking Process Efficiency With AI, and schedule a guidance session or inquiry to explore how to get ready for your AI deployment.