Written by Rob Gold, President, dentsu B2B Global + UK&I
The transformative potential of artificial intelligence (AI) lies not in the assumption that it will redefine marketing entirely, but in how we reimagine its role within our marketing frameworks. By designing Go-To-Market (GTM) strategies that are purpose-built for an AI-first environment, organisations can maintain a competitive edge in an increasingly complex landscape.
Today, AI investment is widespread. Over 90% of businesses plan to increase their AI spending over the next three years. However, only 1% of these organisations consider themselves to have reached AI maturity. This discrepancy highlights both the opportunity and the challenge - we are in control of how we navigate this evolving AI journey.
At dentsu B2B, we often explore the role of various AI modalities (generative, predictive, experiential, and efficiency-driven) in driving tangible business outcomes. The goal is consistent; to leverage AI to create measurable impact. Here are four key outcome drivers to help shape a more effective, AI-enabled GTM strategy:
1. Embed vs. Invent
AI enables a shift from reactive decision-making to proactive, real-time action. However, capitalising on this capability requires a fundamental shift in mindset. AI brings new levels of agility to marketing ecosystems; real-time insights, adaptive models, and continuous relevance for high-value prospects.
Ultimately, GTM success often depends on reducing the time from customer inspiration to transaction. As buyer journeys grow longer and more complex, embedding predictive AI into every GTM component allows organisations to influence what can be controlled, thus reducing time to conversion.
Rather than reinventing existing processes, by embedding predictive AI across platforms brands can deliver intent data, competitive insights, and opportunity scoring in real time. This can result in GTM cycles that are up to 30% shorter, enabling teams to align faster and make dynamic, data-informed decisions.
2. Personalisation to Pipeline
While the concept of personalisation is not new, the application of AI elevates its strategic value. The opportunity to use AI to deliver hyper-personalised, omnichannel experiences can lead to higher engagement, lower customer acquisition costs, and has resulted in >35% increases in deal velocity
The opportunity today lies in shifting from AI for efficiency to AI for experience. Too often, customer interactions with digital ecosystems remain functional rather than inspirational. Few visitors arrive at a website seeking inspiration; rather, they come to transact. This represents a missed opportunity to influence the buyer journey at its earliest stages.
Our B2B Superpowers research found that delivering a seamless initial experience can reduce the sales cycle by up to 16 weeks, and AI plays a pivotal role here. While chatbots and virtual agents are commonplace, their potential extends far beyond customer service. By designing native AI experiences that curate real-time, personalised content, businesses can better engage buyers, accelerate pipeline development, and close deals more effectively.
3. Revenue Intelligence
AI is transforming how organisations forecast revenue, retain customers, and identify cross-sell opportunities. By integrating AI into revenue intelligence systems, companies can not only respond to customer behaviour but also anticipate future needs.
The impact of AI-powered revenue intelligence is huge. Today, platforms already exist that use AI to score leads, predict churn, and uncover expansion opportunities; automating what was once manual, reactive work. This can drive significant results: we’ve seen increases in customer lifetime value by >40%, achieved by delivering the right offer at the right moment (often before competitors even realise the opportunity exists).
4. People-Powered Transformation
A well-known adage states: AI won’t take your job, but someone who knows how to use it better will. More accurately, businesses that leverage AI more effectively will capture market share and customer loyalty faster.
People remain the most critical enabler of AI success. However, a skills gap persists. Leaders are 2.4 times more likely to cite employee readiness as a barrier to AI adoption. Meanwhile, nearly half of employees say training is essential for AI adoption, yet many feel under-supported.
When executed effectively, the impact is substantial. We see businesses already acting here by not only developing the foundational infrastructure for the AI era but are also equipping marketing teams to operate fluently within this evolving landscape. This includes a deliberate investment in workforce upskilling, fostering cross-functional collaboration between marketing professionals and technologists. This in turn enables their teams to articulate more sophisticated, insight-driven narratives around complex technologies.
In an AI-driven world, human skills such as critical thinking, empathic leadership, and decision-making under pressure are more important than ever. At dentsu B2B, we are working to close the capability gap by creating AI tools that make data accessible, building agents that democratise insight and enable teams to act with speed and confidence.
Where to go from here…
To future-proof an AI-powered GTM strategy, leaders must focus on four outcome drivers: Embed, Personalisation, Revenue, and People.
AI should not be viewed as the strategy itself, but as an accelerator of strategic goals. GTM strategies must remain rooted in customer-centricity, supported by a clear vision and thoughtful AI adoption choices.
Rather than chasing technology trends, businesses must align AI investments with the outcomes they seek to achieve. In doing so, they will ensure their GTM strategies are resilient, relevant, and ready for the future.
Contact us if you’d like to discuss your B2B brand’s current challenges – we are always happy to explore how we might assist.
Source:
https://www.bigmoves.marketing/blog/blueprint-for-transforming-b2b-saas-growth-with-ai-tech