Agentic AI for Go-to-Market Teams: Marketing, Growth, and RevOps

Let’s explore how Agentic AI can supercharge your GTM team by automating the tedious stuff and giving you real-time insights—so you can focus on what really matters!

What is Agentic AI for GTM teams at small to mid-sized orgs?

According to desk research, ChatGPT prompts, and some definition clarity seeking, Agentic AI streamlines various manual workflows and tasks that take up way too much manual time.  Examples include customer segmentation, personalized outreach, lead enrichment and market research to drive efficiencies. This gives teams time back to focus on high value work. 

AI also helps analyze the data. With fast data-driven insights, teams can "about-turn" faster, and hone-in on the programs that are performing and converting. No more waiting for weeks to hear back from your data scientist team or an outsourced operations group. AI gives you instant answers so you can allocate resources to what's working.

AI is particularly beneficial for smaller teams that don't have extensive resources and not only helps with automating routine tasks but also provides strategic recommendations-based on real-time insights.

This article distinguishes what is real in terms of AI Apps being deployed by GTM and how you can get started and also more fully embrace AI.

For context, according to Andrew Ng's Build event keynote in late 2024 "AI is the new electricity", and while electricity is powerful, the true value is realized when you channel the power to drive meaningful value. This is true for AI. When you build an App that uses AI to perform all the tasks for you. Electricity powered machines so that humans could focus on cognitive tasks. AI takes this a step further by doing the taxing, repetitive tasks. The humans then do creative problem-solving, further innovation through ideation and also build deeper connections that can change the shape of a business.

Understanding Agentic AI

To explain this, let's break down what "Agentic AI" refers to, and discuss its key characteristics.

Agentic AI refers to artificial intelligence systems that can act on behalf of a user or another system with some degree of autonomy.  AI Apps or an AI system can make decisions and perform actions without human intervention, based on the programming and learning algorithms they have been equipped with.

Key Characteristics of Agentic AI:

1. Autonomous: They operate independently within a set framework or guidelines. They make decisions based on the data they process without needing step-by-step input from humans. Yay! Doing the work in parallel, while teams focus on other important tasks.
2. Adaptable: They can adjust their behavior based on changes in their environment or in the data they receive. This is particularly useful for GTM teams as the data is constantly changing. Whether measuring paid channel performance or inbound traffic conversions, conditions constantly change
3. Proactive: Unlike passive systems that require direct human commands to operate, agentic AI can initiate steps based on a scheduled workflow that, say, runs every Monday morning. This proactive approach is crucial where you need to be fully prepped for, say, a weekly or monthly meeting.
4. Goal-oriented: Agentic AI systems can be designed with specific goals. They prioritize tasks that align with these goals and make decisions that further their progress towards achieving them.
5. Interactive: The beauty of these AI systems is they can interact with many other systems for example read a .wav file or scrape a website. What's more they can also interact with humans, who can remain fully in control, modifying for a specific set of actions or configuring for a unique data-set.

When a GTM team is getting started using AI Apps and workflows, they can stay in control and make decisions on what exactly needs to be automated. Which tasks and which steps.

Once you’re satisfied with the result output and efficiencies, you then broaden scope and also schedule to run at a regular cadence. The possibilities are endless. Start with a controlled scope, learn, adjust and then expand.

Real-World AI Apps in Go-to-Market Strategies

A. Data Insights for Faster Answers & Quick Decisions

GTM teams have a lot of data. Our tools and systems track and update constantly. From Google Analytics, Google Ads, Google Tag Manager to Hubspot forms and Salesforce pipeline opportunities as they move down-funnel, there's a ton of data spread across many systems. Even with a limited set of KPIs, you still pose new questions as you progress through the quarter or half. AI will detect anomalies in your data and give you a summarized report that explains why something is anomalous. This saves a huge amount of time and effort trying to analyze irregularities.

What if you could easily chat with a specific set of data for immediate answers and insights. This is now possible. Simply upload a .CSV file from your run-the-business systems and chat with any question you need answers to, typing a simple English prompt. Alternatively, connect directly to your database or warehouse such as Snowflake, Postgres.

As with any rich set of data, questions beget more questions. The beauty of having this chat capability means you don't have to prepare hours or days ahead and when you're making important decisions, you're not basing it on yesterday's reality or worse, last week's position. Get so much time back and let AI answer your questions in minutes.

Here's pipeline and revenue questions you could ask for instant results and charts to share. No data wrangling and trying to read or understand huge spreadsheets.

• "What are the top use-cases that converted to a closed won deal?"
• "What paid channels have the highest conversions and calculate the average CPL?"
• "For closed new deals, what's the ASP by territory and rep?"

You get the idea.

Being able to ask live questions is pure gold. You could bring this feature to a meeting and get instant answers. Meetings run faster and teams are empowered to move forward with decisions.

B. Automate Repetitive Tasks

The automation of these tasks allows teams time to focus on more complex work that requires critical thinking and personal attention. 

Automated emails or touches can be set to run at cadenced intervals. Moreover, these messages can now be personalized based on the recipient's previous interactions, or role within their org, which yields higher engagement.

Even simple steps such as preparing your target account and contact list, such as enriching fields including industry, org size, geo locations can significantly speed up execution and also validates who you're sending communications to. 

C. Enhancing Pipeline Conversions

Many of your target users and buyers are active on social channels such as LinkedIn and an ideal way to engage is via messages or posts on their preferred channel. Let's say you just finished a really engaging webinar workshop and it's posted on your YouTube channel and you'd like to point some of your fave customer users to it. Let an AI App do the leg-work to transcribe and create copy for a social post. Make it relevant, engaging and what's more get it out fast.

Meet users where they are at, give them relevant and engaging content that will convert and drive pipeline.

Start with a prebuilt template that walks you through it easily. 

Separating Promise from Reality

While many GTM teams experiment with AI tools including LLMs such as ChatGPT, they may still have some hesitancy implementing "real-world" use-cases. The first step is to get aligned on which process or set of tasks you want to AI-run and then set expectations on the desired output. 

Often the issue lies with how to integrate with existing systems and apps. Teams often struggle with adapting their current processes to accommodate new AI tools, which can disrupt productivity and lead to resistance.

To overcome this, start by downloading the data you want to work with and input or upload via .csv or perhaps a .wav file (for audio).  If you’re a Gong user, you could also directly connect with Gong or even set up a folder with all your sales calls. Having a simple upload and subsequent "run" capability using a purpose-built App is the best for immediate results. Then, get more adventurous and configure exactly what tools and systems you want to integrate or operate as part of a workflow, designed for specific tasks.

Another significant challenge is the skill gap. Some teams believe that you need technical expertise to develop, maintain, and effectively integrate. That is not the case. There are certainly some tools that do require some technical skills, such as Clay.com and for this reason, teams outsource to a freelancer or consultant. That can also take more time and cycles to get right.

However, if the solution provides pre-built AI Apps out of the box that you can easily run and consume, then you become a lot more confident and trustful of AI.

Data privacy and security can also be a concern when implementing AI. If the solution you are choosing from a vendor takes care of security measures and compliance with data protection regulations, then you are safe-guarded rather than going it alone and trying to build from scratch and cobble together some capabilities on top of an LLM.  

Finally, achieving team alignment and buy-in is essential for the successful adoption of AI Apps. Change management strategies need to be considered for a culture that embraces tech and to alleviate any possible fears of replacing human jobs.

Future Prospects of AI in Go-to-Market Teams

A time will come, in the not-too-distant future where GTM teams don't even proactively talk about "which AI App or tool should we deploy" because it will become second-nature and the team will have their fave default Apps or tools on their dashboards.

A recent AI Section webinar discussed how marketing teams will reduce in size because AI will take over a lot of the current manual tasks. However, the good news is it will actually free up teams to work on high value work, which doesn't necessarily mean that humans will be replaced. 

As technology evolves, these tools will become increasingly integral to developing effective market strategies. 

Conclusion

AI tools will become integral and second nature for GTM teams. Small and mid size teams will adopt and move fast, with AI taking over manual tasks, enabling teams to focus on higher-value work.

In fact AI will likely replace or at least consolidate fragmented, multiple SaaS tools. Your AI agent can be configured to your unique needs for the whole enterprise. In this way GTM teams will move much faster by working together with any AI counterparts in the org. 

The focus will shift from choosing AI tools to maximizing their potential for strategic growth.

Agentic AI offers a powerful combination of automation, adaptability, and real-time insights to empower GTM teams, transforming workflows and accelerating outcomes. That usually means pipeline and revenue.

At MarkovML, we’ve been listening very closely to the market and the needs of our users inside GTM teams at growing, scaling orgs and their number 1 challenge is to better understand what’s actually working and using data-driven insights.  The 2nd order of business then has to be around how to automate those repetitive tasks so teams work at high efficiency.

Last year's AI promise is now today’s AI reality and it comes in the form of pre-built AI App and Workflow templates, ready to dive in and see results in seconds to minutes.

I’d love to hear your thoughts and how you are embracing AI capabilities today. Contact me at: pankaj@markovml.com