Uniting Marketing and Tech Teams to Unlock AI Success

The majority of marketing and tech teams have historically been siloed within organizations, with each focusing on their own goals and paths for execution. Now, as the adoption of AI to enhance customer experiences and drive greater results takes off, that separation is no longer sustainable.

In fact, according to McKinsey, nearly 65% of marketers use AI, but “many struggle to reach a point of inflection where they can scale AI’s impact.” Additionally, teams often fail to communicate or understand objectives and needs across departments. This disconnect warrants enterprises fostering close collaboration between marketers and tech teams to maximize the benefits of AI.

Why AI success hinges on collaboration

Marketers are adept at understanding their audiences and identifying ways to reach them. AI tools can amplify these skills, but to get the most value and accurate results from AI, marketers must overcome the gap in data and AI literacy education by developing the skills to prompt and optimize AI tools.

Thankfully, the growing bottom-up use of ChatGPT by consumers fosters an initial comfort level with AI for many marketing professionals—but this casual use is not enough for leveraging enterprise-grade AI for content creation, optimization, and compliance. Enterprise tech teams, on the other hand, are proficient in data and AI but often lack awareness of company-wide go-to-market objectives, nor the speed required to pivot or compete. As engineers and developers focus on their own tasks, their understanding of marketing objectives and execution remains surface-level.

It seems simple. Better collaboration across an organization’s departments leads to successful AI outcomes in an ultra-competitive market. But anyone who’s familiar with change management knows that’s easier said than done. Reinventing, trialing, adjusting and adopting internal processes to effectively put to use each team’s specialties and getting them used to working together regularly, is a huge change.

Marketing must take some time to understand how the data tech teams’ role could be relevant to marketing pursuits, and what solutions are out there that help marketing teams. Tech teams need to take some time to understand marketing’s pain points, as well as how they measure success and their goals. They also have to update their traditional ‘ways of working together’ to remain in lock step. Once they are more open to each other’s needs and capabilities, they can collaborate to drive the business forward.

By prioritizing breaking down silos and supporting each other, marketing and tech teams can bridge the gaps to remain competitive. This involves marketing teams getting more familiar with technical terminology and concepts to participate in conversations and tech teams leaning into more agile and quick-turn processes, rather than elongated and complex rollouts.

My team, for example, has found that our customers see the greatest success in implementations, measured by adoption and realized impact, when we have cross-functional stakeholders. When marketing teams are combined with a highly involved technical team to support defining an engagement, monitoring progress, and leaning in to understand aspects they may not traditionally own, the business sees greater results.

To unlock the value of AI, marketers and tech teams need to work together. This starts with ensuring members of both departments are involved from the beginning stages of adoption.

A lesson in specialized AI

To take full advantage of AI’s potential, marketers need to be aware of the differences between generic and specialized AI tools. While it can be faster to adopt and use generic AI tools, such as ChatGPT, more likely than not, these won’t deliver maximum value for an organization. That’s because if you only rely on generic tools, such as the content capabilities within your everyday enterprise suite, you may miss out on performance and compliance benefits that other types of AI tools deliver. In addition, because generic AI tools are built on open-source models, security concerns and hallucinations are a real risk.

On the other hand, there are purpose-built AI tools that can ingest brand guidelines and are grounded in LLM, ML and applications layers and are designed to meet the performance and compliance needs of marketers. They embody martech stack integration, adherence to regulatory and brand compliance, security, audience segmentation, personalization capabilities, and rapid experimentation. Such specialized tools have accumulated a deep, specialized knowledge base, help to speed legal content approvals and reduce risk.

Ultimately, marketers should prioritize investing in AI tools that drive measurable impact for their business. Keeping a watchful eye on where AI is creating the most value—from increased clicks and transactions to growth in brand loyalty—will be crucial, especially as marketing departments face potential budget constraints.

Setting your organization up for success

Collaboration requires buy-in from data and marketing teams who must start to get familiar with functions outside of their specialty. Before your organization even embarks on an AI implementation, be sure to include both marketing and tech teams in investment and strategy discussions. Early collaboration between marketing and IT will ensure that AI tools are aligned with each team’s needs and make for smoother adoption and process fine-tuning.

Once you’ve narrowed down a solution, collecting feedback from each team early on will be extremely valuable. Tech teams can pinpoint bottlenecks, compatibility or stability issues and areas for improvement to drive greater efficiency. Marketers, meanwhile, can apply results from AI experimentation for campaigns, analyzing how outputs are driving engagement, impacting sales, and building stronger customer loyalty. These early metrics will quickly inform the organization about the ROI of their AI tool(s) so they can determine the best AI strategies to replicate. To ensure new capabilities drive efficiency and deliver value, marketers must be open to new approaches and have some understanding of how the technology works.

AI adoption can drive significant value for organizations across operations and marketing functions, but it requires agility, communication and shared knowledge across departments. AI-driven marketing success is within reach but first, you may need to check in with your tech colleagues.