AI is running the B2C buyer journey. Most marketers are still sprinting with their eyes half closed

AI is no longer a pilot. It is the plumbing of the buyer journey

The report lands with a clear premise: AI is already rewiring how consumers discover, compare and buy, and how marketers are supposed to track and influence every step of that journey. Discovery starts inside AI interfaces, decisions zigzag across clicks, chats and calls, and brands are racing to plug AI into each one of those touchpoints. 

Invoca surveyed 600 B2C marketers in US companies across categories like auto, healthcare, finance, home services and travel, all at manager level and above. The sample makes it less of a hype survey and more of a ground report from people who actually carry revenue targets. 

What comes through is not confusion. It is something more interesting, and more risky: optimism running ahead of operational reality.

Force 1: An atmosphere of optimism and urgency

Marketers are not reluctantly accepting AI. They are betting their careers on it.

• 92 percent are optimistic about how AI is changing marketing.

• 84 percent say AI is making their work more strategic.

• 81 percent think the AI winners in their category will be decided in the next 12 months.

• 80 percent feel leadership is pressuring them to show AI wins quickly. 

So you have an industry that believes this is a leaderboard year, not a test year. Nobody wants to be the team that underplayed AI and missed their 2026 targets because they were “being careful.”

But there is a human cost. Three out of four marketers say they often feel stressed about keeping up with AI, even though 88 percent say they are ready to lead if their company doubles the pace of deployment. 

In other words, the energy is there. The anxiety is there. The bar is high.

Force 2: Money that signals belief, not yet alignment

If you look at budgets, you see belief in AI. You also see a disconnect between the story everyone is telling and the way the money actually moves.

• 90 percent of organisations plan to increase AI spending next year. Only 1 percent plan to cut it.

• Yet 68 percent allocate 20 percent or less of their martech budget to AI, even though 80 percent admit pausing AI would put 2026 targets at risk. 

On top of that, 28 percent of marketers already feel their company is spending too much on AI, while only 5 percent think it is not spending enough. 

That is not what disbelief looks like. That is what “we are spending, but we are not sure it is working” looks like. The report spells out the usual blockers - funding constraints, privacy and compliance, difficulty proving ROI, dependence on agencies, and a lack of training all hover around the 27 to 29 percent mark. 

For leaders, this is the first tension to resolve. You cannot tell your teams “AI is existential” and then starve the stack, or scatter budget across tools nobody knows how to use.

Force 3: Overconfidence and the speed gamble

The sharpest insight in the report is how confident marketers are about where they stand. So confident that the math breaks.

• 82 percent believe their organisation is adopting AI faster than its closest competitors.

• 59 percent say they are “somewhat faster” and another 23 percent say “much faster.” 

Statistically, that cannot be true for everyone. It means a lot of teams are operating on a distorted map of their market.

That confidence leaks into risk appetite. When forced to choose, 56 percent of marketers would rather move quickly with AI even if it risks harming customer experience, than move cautiously and be outperformed by competitors. At the same time, 74 percent agree that rushing AI does hurt customer experience. Yet 84 percent are confident they personally can scale AI fast without harming it. 

So the story in most organisations sounds like:

Rushing is dangerous for others. We can handle it.

That mindset shows up in deployment posture too. Only 15 percent say they are in cautious, watchful pilots. Everyone else is either moving “fast but controlled” or “sprinting” and accepting the risk that comes with it. 

The gaps that are quietly leaking value

Beyond mindset and money, the report spends a lot of time on where AI is actually plugged in - and where it is not.

AI is now common in measurement, ad optimisation, personalisation and chat. More than 40 percent of respondents report using AI for things like chatbots, recommendations, dynamic offers, ad optimisation and creative testing. 

But two gaps stand out.

1. The unstructured data blind spot

Marketers love text that feels “digital” - reviews, search queries, chat logs, emails. Over half are mining these with AI. Yet only 37 percent are using AI on call recordings and transcripts, even though calls are where you often get the clearest intent, objections and emotional context. 

That means the most honest part of the buyer journey - where people say what they really think to an agent - is still largely invisible to the models guiding spend and experience.

2. The insight to action lag

Even when teams do analyse calls, the data moves too slowly. Only 21 percent can send call conversion data back into ad platforms in near real time. Most rely on daily batch uploads. The operational lag is worse on action: just 2 percent can act on a new insight from call data within a day, while 75 percent take two to seven days. 

In a world where audiences and auctions reprice by the minute, this is like steering a Formula 1 car using last week’s GPS.

The most dangerous gap is not technical. It is emotional

The report then forces a hard comparison between marketer belief and consumer reality, using Invoca’s own B2C buyer research as a reference.

• 85 percent of marketers think consumers feel positive about AI interactions. Only 37 percent of consumers actually do.

• 86 percent of marketers believe AI is improving the buying experience. Only 35 percent of consumers say AI made their experience better.

• 49 percent of marketers think consumers prefer AI for complex, high stakes issues. Only 30 percent of consumers are confident AI can resolve such issues. 

This is the part that should make leadership pause. You can fix budgets, data pipelines and training. A gap this wide between how you think customers feel and how they actually feel is a threat to brand trust.

It also explains why so many AI journeys feel slightly off even when the metrics look good. If the models are trained on internal assumptions and partial data, they will optimise for what the organisation wants to see, not what the buyer is really experiencing.

So what should marketing leaders actually do with this?

The report ends with four strategic imperatives that are worth lifting out and turning into action items. 

1. Audit your reality, not your narrative

   Commission an honest view of where you sit on AI maturity against peers. Use external benchmarks, not internal optimism. Treat any “we are ahead of most” claim as a hypothesis that needs proof.

2. Align ambition, budget and enablement

   If AI is genuinely critical to 2026 targets, revisit martech allocation. Either increase the share going to AI capabilities or narrow the ambition to match what you are funding. Do not ask teams to deliver AI outcomes on experimental budgets and fragmented tooling.

3. Make insight to action your primary KPI

   Track not just what data you have, but how fast it can change a live campaign. Prioritise integrating high value unstructured data like calls, and design systems where signals can update bids, audiences and journeys in near real time.

4. Close the loop with customer sentiment

   For every AI deployment touching customers, build a feedback loop that pairs behavioural data with explicit sentiment. Collect short post interaction feedback, monitor call transcripts for frustration, and compare that back to your internal scores.

Final thought

The Invoca report paints a market that is moving fast, feels good about itself and is quietly missing some of the harder questions. Optimism is not the problem. Overconfidence is.

The B2C brands that will actually win the AI decade are not the ones shouting “we are ahead” the loudest. They will be the ones doing the unglamorous work of fixing data blind spots, cutting latency, aligning budgets with reality and listening far more closely to what their customers are really saying when the survey link is not in front of them.