I’ll level with you, I often find it overwhelming to try and keep up with the latest apps, products, and trends. From merging vast troves of data to harnessing predictive analysis, and from crafting hyper-personalised customer journeys to automating early brand interactions – the array of choices seems endless, with platforms innovating at different paces and product quality varying.

When considering my own perspective on AI, I decided to take a step back and think about a few areas that promise to be the future of B2B Marketing – Generative AI, opportunities for Customer Experience and Synthesis AI –  considering these, you can navigate towards insights, inspiration and hopefully a little excitement in thinking about AI’s role for you.

Generative AI – the content engine

This is the AI space where mass adoption is taking off, with usage leaping ahead of a decent understanding of the risks and opportunities – creating and refining content using algorithms. It’s where most marketers see a really prolific amount of discourse from peers; ChatGPT and Dall-E screengrabs, prompt engineering tips and tricks shared on social feeds and excitement about the impact on content creation at scale.

As B2B marketers – particularly those working with the complex needs of enterprise audiences – we love a low lift, high impact workflow. That’s certainly the pull for much of the generative AI functionality available – but woven throughout key usage trends, one thing is clear: the role of the human as oversight is absolutely critical. 

Thinking about what we show our audiences, three big opportunity areas – keyword research, content development and data analysis – come with fresh challenges for people and process. An over-reliance on AI might not just optimise based on keywords out of context, but could also include terms that impact brand reputation. In content development, AI tools can accelerate production and time-to-market, but this introduces risk for cultural relevance, sensitivity and accuracy. In understanding communities and trends amongst large datasets, comes increased risk of biases – sometimes biases that have been trained into AI models. There’s also the more simple risk of creating bland, unoriginal content that is a hash of material existing elsewhere on the internet.

This all has one big (and promising) implication; how we work together as a result of these dynamics will need to change. Consider now how your teams can validate AI outputs, with new procedures, workflows and health-checks – this offers exciting, fresh project management and Quality Assurance opportunities in B2B marketing.

Using AI to enhance customer experience

Right at the heart of any B2B marketer’s role is the same priority – achieve growth by getting the right information in front of the right people, as seamlessly as possible, at the right time.

AI has been powering fantastic experiences centered on the customer with platforms like Drift offering chatbot and cloud-based hyper-personalisation products bolstering every stage of the buyer journey – particularly in transforming buyers’ early interactions with B2B brand properties such as landing pages. Platforms like this also help enable sales teams to optimise their human hours smartly, offering orchestration tools that focus on timely, data-driven conversations and efforts that convert. 

If you’re at an early stage in planning where AI can play a role for your brand, consider how AI could offer little wins in your buyer experience on key metrics, like increasing time spent on pages, reducing user friction in reaching key assets or optimising the length of the sales cycle.

Synthesis AI – the insights engine

Acting on key signal moments is incredibly impactful in B2B marketing – it’s that niche research insight that powers better brand awareness targeting with unique personas. A sentiment shared on a social network, account intelligence trends from the Customer Data Platform, a comment by a Chief Technology Officer on Reddit, trends and language used in company reports – the signals from those making decisions and influencing them are endlessly evolving. Intentify, for example, offers 6 different forms of intent monitoring.

A fascinating analysis on Andreessen Horowitz (hat-tip to DemandBase CMO Jon Miller for sharing this one) electrifies the thinking around how AI could impact better decision-making in directing marketing resources – and particularly in Account-Based Marketing.

The Synth AI Revolution

What if an AI offering could produce decision-aids, product intelligence, key people to contact and when, and concise strategic plays based on analysis of huge, segregated data sets. This can transform enterprise selling with smarter use of the human hours involved in piecing together the holistic parts of a Go-to-Market plan.

“.. one potential manifestation is for AI to identify when a target account is at its highest level of intent (based on news reports, earnings calls, talent migration, etc.) and alert the relevant sales rep. The AI model would then, based on the synthesised research, suggest the one or two most important issues to mention in the email, along with the product features most relevant to that target account.”

Here’s the value an Account-Based Marketing Manager could experience from such an offering:

• An account in Scotland has an emerging hiring surge happening around X job types
• Analysis of earnings calls over the last two quarters and board commentary show they’re about to invest in platforms that do Y
• In industry news the account CEO and CTO have both expressed positive sentiment around things that do 
• In public forums there is negative sentiment for legacy platforms not servicing Y adequately
• Here’s two products that are most aligned to this, with hyper-personalised messaging
• Here’s a sales cadence designed specifically for relevant personas based on analysis of the selling firm’s global nurture performance data

The Account-Based Marketing Manager’s role then evolves from that constant tug-of-war sourcing content and face-time with Sales, to a more focused quality assurance, customer experience and rapid engagement monitoring and action role.

For Synthesis AI readiness, consider working with your sales and marketing teams to map all the account intelligence sources currently in play and the manual or semi-automated workflows currently active in bringing that data together for use in your Account Based Marketing. This will offer you a stronger footing when assessing new AI technology opportunities in this area.

Synthesis AI is most likely to emerge as an offering from the larger orchestration platforms such as DemandBase or Terminus so it’s something we’re watching closely.

Keeping up with trends was tough before this most recent surge of AI adoption and for those of us working in B2B marketing, the continued emergence of new technology and innovations will only increase. Right now, it feels like the B2B innovation landscape is as hot as our counterparts in B2C once experienced. If you’re feeling overwhelmed by the pace of change, consider how Generative AI, Customer Experience AI and Synthesis AI could help you thrive. You’ll no doubt find some interesting rabbit holes along the way.

Related reading: A Shift in the Direction of Planning Where Strategy Leads Technology