How are B2B marketers navigating the AI maze?

Grappling with transformation, tensions, and opportunity

Given the enormous amount of information leaders are consuming about generative AI, few wonder why it dominates conversations—from the kitchen table, to the office floor, to the boardroom. The paradox of these debates, however, is that the more we have them, the less sure we feel that we fully understand AI’s potential and consequences. Lasering onto the marketing function, this has ramifications for the future of the skills needed to drive a business’ brand and customer segments, for example, whilst further complicating the delicate, often fragile, influence marketers enjoy at the C-suite. Many questions remain unanswered for these leaders, therefore.

And so it was that HotTopics brought together nearly 150 marketing leaders for The Studio, where, over 15 concurrent roundtable discussions, these executives discussed their organisations’ AI journeys, how those have parred with expectations, and what that means for their next steps. Compiling many of the roundtables’ moderators’ notes, this article is both a synthesis of these debates and a repository of strategic questions leaders can ask of themselves and their teams.

Of the roundtable conversations? What has emerged is a picture that is both fragmented and revealing: the AI journey is anything but uniform, and there is no single path to success. That offers both freedom for marketers to carve their own journeys, and not a little trepidation as they grapple with an epoch-defining technology on tighter budgets.

Navigating the AI maze

• No one-size-fits-all approach
• Complexity and misalignment at the core
• Fear vs. opportunity: The sentiment shift
• The need for new skills and new thinking
• Looking ahead

No one-size-fits-all approach

As one moderator, Sarah Roberts, Group CMO at Boldyn Networks, noted, businesses are at vastly different stages of AI adoption. Some are racing ahead—one brand has already appointed a Chief AI Officer to spearhead transformation—whilst others, including much larger global brands, are still in limbo, unsure who should take ownership of AI strategy within sprawling, decentralised teams. The diversity in progress is stark, and it underscores a broader truth: there is no definitive playbook for integrating AI into modern business operations.

Key question: Where is our organisation on the AI maturity curve, and do we have the right leadership structure in place to drive transformation?

Follow-ups:

1. An AI strategy based on what we believe competitors are doing is not a strategy at all; how do we maintain a good understanding of the outside world whilst filtering out unhelpful FOMO?
2. Who owns AI within marketing, and does that person have true cross-functional authority?

Complexity and misalignment at the core

David Keene, CMO, Wipro, moderated, too. He highlighted in his notes  the scale of the challenge. Behind the scenes, many companies are struggling to piece together the jigsaw puzzle of operationalising AI. Security, compliance, and IT teams are especially stretched as they grapple with the realities of managing sensitive data and navigating the regulatory landscape. While many organisations share a similar vision for AI’s potential, the path to achieving operational resilience is proving far tougher than expected.

Basic tools like ChatGPT and Microsoft Copilot are seeing widespread use for everyday tasks—meeting summaries, research, and email drafts are now AI-assisted in many companies. But when it comes to more complex capabilities such as segmentation, targeting, and personalisation, AI’s promise remains largely unfulfilled.

One pressing issue is a disconnect between leadership expectations and ground-level execution. Senior executives are often bullish about what AI can achieve, while the teams tasked with delivering results are mired in real-world obstacles that have been years in the making. This gap is fuelling internal friction and making stakeholder management increasingly difficult.

Key question: Have we clearly aligned executive ambition with operational capability when it comes to AI in marketing?

Follow-ups:

1. Do our data governance, compliance, and IT teams have the support they need to enable AI, or are they acting as unintentional blockers?
2. Are we investing in the right areas to close the gap between aspiration and execution?

Fear vs. opportunity: The sentiment shift

During his roundtable, Hugo Drayton, Chair at Boundless, observed that the balance between fear and opportunity is slowly shifting in AI’s favour. Until recently, the emphasis was firmly on efficiency: time and cost savings were the dominant metrics. One participant shared that their organisation’s goal was to achieve a 20 percent increase in productivity, measured almost entirely in terms of time saved. Creative applications of AI, however, have taken a back seat.

The approach to AI remains uneven across the marketing world. Microsoft Copilot appears to be the most widely adopted engine, but enthusiasm and uptake varies significantly. Digitally-native businesses, unburdened by legacy systems and entrenched processes, are adapting far more quickly than their traditional counterparts.

Consumer behaviour is also influencing the pace of adoption. B2C brands are feeling more urgency, as consumers rapidly embrace AI in their daily lives. In contrast, B2B companies continue to trail behind.

Key question: Are we being intentional about leveraging AI merely for efficiency, or are we missing out on its ability to unlock new forms of creativity and/or competitive differentiation?

Follow-ups:

1. Is our AI strategy proactive or reactive to consumer adoption?
2. How can we utilise experimentation and excitement to move beyond incremental AI gains?

The need for new skills and new thinking

As AI reshapes the marketing landscape, one skill is emerging as essential: prompting. The ability to craft effective instructions for AI systems is quickly becoming a core competency for all employees, not just technical teams. This is already different to the 2024 prediction of a new role for business: dedicated prompt engineers. The shift in trends can often give leaders digital whiplash.

Some conversations touched upon sustainability concerns. AI is not just a software challenge; it has real-world implications in terms of energy consumption, water use, and environmental impact. As the volume of data increases, so does the demand for resources to process it.

There were cautionary tales too. One example was Klarna, which replaced a significant portion of its customer support team with AI—only to walk back that decision and reintroduce human support. It is a reminder that not all automation experiments lead to lasting success. Still, testing and learning is the name of the game and pioneers should not pause in their search for fear of being stung first.

Key question: What are we doing to prepare our teams—and ourselves—for the new core skill of prompting and AI orchestration?

Follow-ups:

1. Are we treating AI fluency as a strategic skill, on par with digital or data fluency?
2. How are we managing the environmental and sustainability implications of our AI usage?

Looking ahead

There is an understandable sense of FOMO driving many AI initiatives. Yet, most marketers have yet to truly engage with more advanced forms of AI, perhaps because they have yet to be created. While the awareness is there, practical applications remain anecdotal. Enterprise-wide solutions remain on the horizon.

In the end, the discussions revealed an industry at a crossroads. AI is no longer a futuristic concept: it is here, shaping how some of us work and what we expect from technology in general. But the journey is fraught with challenges, and while the potential is immense, the path forward will demand clarity, patience, and a willingness to rethink everything from leadership to legacy systems.

Key question: Are we shaping our AI roadmap based on hype and FOMO, or on a clear-eyed assessment of value, risk, and readiness?

Follow-ups:

1. How do we ensure the basics of good business practice (leadership, collaboration, brand, customer service) remain front of centre and are augmented with AI, and not pushed to the side?
2. How are we measuring the long-term impact of our AI decisions—including reversibility, workforce implications, and brand trust?