A future-facing conversation about what happens when AI can execute most campaign tasks: media buying, reporting, content variation, targeting, and optimisation. The episode explores whether marketers become less important, or whether their role shifts upward into judgement, positioning, strategy, brand, and customer understanding.

Core questions:

If AI can increasingly execute campaigns, what parts of marketing still require human judgement?

Are marketers at risk of becoming operators of AI systems rather than strategic business leaders?

What skills should B2B marketers build now to stay valuable over the next five years?

A future-facing conversation about what happens when AI starts reshaping the whole B2B go-to-market system: targeting, intent, content, seller enablement, pipeline generation, forecasting and follow-up. The episode explores whether AI makes sales and marketing more aligned, or whether it creates more noise, fragmented messaging and over-automated buyer experiences.

Core questions:

If AI can increasingly identify accounts, generate content and automate GTM workflows, what parts of sales and marketing still require human judgement?

Does AI make sales and marketing alignment easier, or does it create new risks around messaging, governance and customer experience?

How should B2B teams combine fit, intent, engagement and pipeline data to know where to focus human effort?

An episode challenging the obsession with intent data and demand capture. The discussion argues that by the time a buyer is searching, downloading comparison guides, or showing third-party intent, the real battle may already have been won by brands that shaped the market earlier.

Core questions:

1. Why is buyer intent often too late in the B2B buying journey?

2. How can marketers identify and influence future buyers before they enter active demand?

3. What does a good balance between demand creation and demand capture look like?

A direct exploration of one of Adzact’s strongest points of view: not every in-market account is worth pursuing, and not every high-fit account is currently showing intent. The episode contrasts short-term buying signals with deeper structural fit.

Core questions:

1. Why can high-intent accounts still be bad commercial targets?

2. What makes an account fundamentally “good fit” before it shows buying signals?

3. How should B2B teams combine fit, intent, and timing in their go-to-market strategy?

A practical episode on the rising cost and declining efficiency of LinkedIn as a default B2B growth channel. The conversation should unpack why costs are increasing, why targeting can be weaker than marketers assume, and how teams can diversify their media mix without losing B2B precision.

Core questions:

Why have LinkedIn leads become more expensive for many B2B teams?

Where does LinkedIn still work well, and where is it being overused?

What should marketers do instead if they need efficient demand creation at scale?

A discussion about the gap between marketing productivity and actual commercial growth. AI can help teams produce more content, launch more campaigns, and analyze more data, but that does not automatically create differentiated positioning, better targeting, or stronger demand.

Core Questions:

* Why does more marketing output not necessarily translate into more growth?

* What are the hard problems in B2B growth that AI does not automatically solve?

* How should marketing leaders avoid confusing efficiency with effectiveness?

A big-picture episode on the future of B2B marketing as execution becomes increasingly automated. The central argument is that brand, narrative, trust, taste, and market understanding may become more important precisely because the mechanics of marketing become easier to copy.

Core questions:

If AI commoditises execution, does brand become more important or less important?

What will separate high-performing B2B marketing teams from average ones by 2030?

How should marketers build brand in categories where buyers are rational, risk-averse, and under pressure to prove ROI?

A commercially sharp episode about wasted spend in B2B paid social: poor-fit accounts, irrelevant impressions, vanity clicks, broad targeting, and optimisation against the wrong signals. This should feel diagnostic and practical, with a clear link to improving pipeline quality rather than just reducing media waste.

Core questions:

Where does most wasted spend in B2B paid social actually come from?

Why do platforms optimise towards engagement rather than commercial fit?

How can marketers distinguish between cheap clicks, real demand, and future pipeline?

An episode about how AI and automation change demand generation without eliminating the need for human strategy. The conversation should position automation as a way to remove manual work while making human judgement around category, customer, creative, and commercial priorities more important.

Core questions:

What should demand generation teams automate, and what should they deliberately keep human?
How does the marketer’s role change when targeting, activation, and optimisation become more automated?
What is the human edge in a world where every competitor has access to similar AI tools?