#NavigatingGenAI Series: Article 1

Navigating the next phase of generative AI in marketing: Insights from industry leaders

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This post-roundtable article reveals critical insights for marketing leaders navigating the next phase of AI adoption. Key takeaways include the need to move beyond siloed AI applications, strategies for measuring AI ROI, the importance of cross-functional collaboration, and practical steps for implementation such as the 'pyramid exercise' and customised AI tools. Participants stress the significance of aligning AI initiatives with overall business strategy and fostering a culture of experimentation. The discussion highlights that successful AI integration requires a balanced approach, preserving human creativity while leveraging AI's capabilities to drive marketing excellence.

As generative AI continues to reshape the marketing landscape, organisations are grappling with how to move beyond initial use cases and integrate this transformative technology more broadly into their operations. To explore these challenges and potential solutions, TechPros.io recently convened a roundtable of marketing leaders, sparking a lively discussion on the future of AI in marketing.

Maria Martyak Strategy Director, Doyle Blackfriars

Sharon Forder CEO, Revop

Jamaica Lancee Head of Marketing, Sensat

Tim Bond CEO & Founder, CogniScale.pro

The challenge: Moving beyond early adoption

Maria Martyak, a marketing strategist, kicked off the roundtable by introducing a critical challenge facing many organisations today: how to progress from the early adoption phase of generative AI to more comprehensive integration across marketing functions. Maria noted, "Right now, organisations are at the early adoption phase of generative AI. We've seen the introduction of generative AI and the early-stage use cases. And now, organisations are largely focusing on content ideation, imagery generation, etc."

The real challenge, however, lies in moving beyond these initial applications. Maria elaborated, "As we move deeper and past that phase and into broader scale adoption of AI into more horizontal activities across the marketing function like ABM, product marketing, and RevOps - and how we look at ROI and ROI measurement - that's essentially the next challenge."

This sentiment set the tone for a discussion that explored the complexities of AI integration, measurement, and strategy alignment in marketing.

Measuring ROI and aligning with business strategy

A key concern raised by participants was the challenge of measuring the return on investment (ROI) of AI integration across different marketing functions. Sharon Forder, a marketing strategy consultant, posed the question: "How do you measure the ROI you get from the investment made in AI, being embedded in your processes? But also, how do those data-driven insights that you get from AI influence your overall strategy and goals?"

The discussion revealed that many organisations are currently focused on efficiency metrics, primarily time and cost savings related to operations. However, as Maria pointed out, "In terms of impact on sales revenue and the entire sales pipeline, client retention is not particularly there yet."

Jamaica Lancee, a product marketing leader, shared an innovative approach to quantifying AI's impact: "I've been toying with something simple which resonates well: it's as simple as actions in model/tool times value. Discuss with your team what value Gen AI adds, which could be in terms of time saved or reduced need for approvals. This generates a number which might be up in the air but agreed upon by the team, providing a simple metric."

Breaking down silos: The key to effective AI integration

A recurring theme throughout the discussion was the challenge of fragmented AI implementation across different marketing functions. Maria Martyak noted that various teams within marketing often use AI tools and softwares for different purposes, leading to siloed solutions and fragmented data sets.

To address this issue, several strategies were proposed:

Cross-functional workshops

Maria shared her experience of facilitating open workshops across various teams, helping to understand use cases and decide which should be escalated to senior management.

Customer journey mapping

Jamaica emphasised the value of this exercise: "Conducting a customer journey exercise helps us understand the misalignments, which weren't the initial intention but pave the way for strategies like ABM (Account-Based Marketing)."

Internal AI ambassadors

Sharon suggested: "Introducing ‘AI ambassadors’ within the organisation could help foster this culture of innovation, reducing fear and encouraging experimentation across the board."

The role of AI in product development and innovation

An interesting point of discussion was the role of AI in product ideation and development. Maria Martyak noted that while AI is being used extensively in areas like coding and content creation, product ideation and development still largely remain human-led processes.

However, the discussion revealed a missed opportunity in leveraging product usage data for innovation. As Maria explained, "We're not looking at product usage data as something to say, 'let's create a new or adjacent product,' which is largely a mistake in a lot of tech organisations."

This led to a broader conversation about the need for better data integration and the potential for AI to play a role in synthesising insights from various data sources to inform product development.

Fostering a culture of AI innovation

Creating a workplace culture where AI is seen as a collaborative tool rather than a threat emerged as a key challenge. Tim Bond, CEO of Network Sunday, emphasised the importance of experimentation: "Everyone needs to be experimenting because if they don't, organisations will be held back by those who haven't grasped the foundational knowledge and understanding of what the opportunity for change is."

Jamaica Lancee shared her approach to addressing these concerns: "I made it a fun thing initially because we weren't sure what we were getting into. Now, we compare how we do prompts because some are showing much higher quality outputs, again emphasising the importance of the input provided."

Practical steps for AI implementation in marketing

The roundtable participants shared a wealth of practical approaches for integrating AI into marketing workflows. Jamaica introduced the concept of a pyramid exercise, explaining, "The whole idea is to figure out what the core activities of each function are and break them down into very human-led, top-of-the-pyramid, big chunk activities. Then, you identify the medium activities and, most importantly, the lower activities, which are the recurrent, consistent tasks that no one really likes but are necessary for the function." Jamaica also suggested customising AI tools, noting, "You can customise your ChatGPT by feeding it your internal documentation to produce more company-focused outputs."

Building on this, Tim Bond highlighted the importance of developing and sharing effective prompt libraries across teams. Tim also emphasised the need for top-down drive in AI implementation, stating, "It's got to be driven from the top down, seen as a transformation programme. Anything involving silos needs a holistic strategy, a CEO-sponsored initiative."

Addressing the challenge of securing executive buy-in, Sharon Forder proposed a practical approach: "Rather than trying to eat the elephant whole, you position it as a trial project. Maybe identify an area in your organisation where you can conduct a test pilot. Implement the pilot, learn from it, and then roll it out across the business."

Maria Martyak advocated for cross-functional workshops, sharing her experience: "At previous organisations, we facilitated this through open workshops, not just for marketing but for various teams, shared on the general Slack channel. This helps us understand use cases and decide whether these should be escalated to senior management." Maria also stressed the importance of aligning AI initiatives with overall business strategy, noting, "Understanding your strategy first and then figuring out where to implement AI is very interesting."

Conclusion: Navigating the path ahead

As organisations move beyond the initial excitement of AI and into more strategic implementation, the key lies in breaking down silos, aligning AI initiatives with business goals, and fostering a culture of experimentation and innovation.

The discussion highlighted the need for a balanced approach that leverages AI's capabilities while preserving human creativity and strategic thinking. As Maria aptly put it, "We're still in Phase One, figuring out how to push people internally towards what Phase Two looks like. Breaking the silos first and understanding AI’s impact is key."

As the AI revolution continues to reshape marketing, many organisations find themselves at a crossroads. The insights shared in this roundtable provide valuable guidance for navigating this complex landscape, emphasising the importance of strategic thinking, cross-functional collaboration, and a willingness to experiment and learn.

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