AI That Actually Moves The Numbers in B2B

‍‍
‍Let's set the scene... Ibiza, Agency Hackers, and a very modern hangover

‍
Rooftop welcome drinks, the evening before the summit. Three hundred delegates swapping war stories, watching the sun fold into the sea, all quietly plotting how to be bright-eyed for Mark Ritson in the morning. Year three for us. We knew the drill, so we looked after the room, partnered with Rebound Recovery, and dished out prepare and repair packs. In exchange, we asked two questions:

1. What is your ultimate hangover cure?
2. What is the biggest headache in your business right now?

The first got the classic responses. Coffee, carbs, denial. The second cut deeper. A clear 68 percent said the real headache is AI gimmicks over substance. Close behind were vanity metrics steering decisions, with spray and pray content and fuzzy positioning not far away.

Different cures. Same symptoms. Noise over signal.

‍

What this means for you..

‍
The cost of AI gimmicks rarely lands as one scary bill. It leaks. On the face of it things look fine. Dig deeper and you see pressure dropping at the tap.

• Time disappears into pilots that never graduate
• Decision quality dips because teams track what is easy to move
• Confidence erodes and next quarter needs a new magic trick

Meanwhile, a disciplined competitor is shaving minutes off response times, fixing errors, and tightening the customer experience. It looks dull. It compounds. Then it wins.

Why we still fall for AI gimmicks, and how to stop

‍
Gimmicks are bad for business. They win airtime because the system rewards the wrong things.

New tools create motion, not progress

Shiny tools make it easy to do more. More drafts. More prompts. More dashboards. It feels productive because things are moving. Progress is when a step in the buyer journey gets faster or converts better.
‍
- What this looks like
Your team ships five AI-assisted blog posts a week. Sessions go up. Sales calls do not.
‍
- What to do
Pick one workflow close to revenue. Define a single metric. Reduce time to qualified demo by 20 percent, for example. Only keep the tool if it helps that number.

‍

Dashboards reward easy wins

It is tempting to chase numbers that rise quickly. Clicks, impressions, time on page. They look great on a Friday update. They do not prove value.

- What this looks like
A help bot boosts “issues resolved” because it answers easy questions. Escalations still take days. NPS is flat.

- What to do
Track one hard metric alongside any proxy. Pair “issues resolved” with “time to human resolution” and “repeat contacts.” If the hard metric does not move, the win is not real.

Announcements beat plumbing

Launch posts and “we built an AI thing” get attention. The quiet work that fixes data and copy gets ignored, even though it moves money.

- What this looks like
You announce a “sales assistant.” It drafts emails from old decks. Reps still fix claims, pricing, and integrations by hand.

- What to do
Update the source of truth first. Pricing rules. Security answers. Integration notes. Then let AI draft only from that verified library. Announce the result when cycle time drops, not the tool when it launches.

AI is not the problem. Habits are

Tools are neutral. Habits decide whether they help or hurt.
‍
- What this looks like
Prompts get shared, not briefs. Pilots never end. No one sets a stop rule.

- What to do
Use a one page brief. Name the owner. Set guardrails. Put a week six decision in the diary. Small scope. Real choice.

Prepare well and you learn more

Good prep makes impact measurable.

‍
- What this looks like
Before the change, you log the current time to first response and the three most common failure modes.

‍
- What to do
Write the baseline and the target on the brief. Agree the sample size and review cadence. You will know if it worked.

Repair fast and you do not lose the day

Fix live issues quickly so small defects do not snowball.
‍
- What this looks like
You sample ten AI outputs each week. Two show the same mistake. You correct the source and it never repeats.

- What to do
Make a short “top three fixes” list every Friday. Ship them. Share them. Momentum builds.

‍

The shift you are aiming for

From performance theatre to measurable lift.
‍

- What this looks like

• Before: “We launched an AI assistant.”
• After: “First response time fell from 3h 20m to 47m with no rise in errors.”‍

- What to do
Tell those before and after stories. One slide. One number. One change. Then scale the wins.

From noise to movement: the playbook

So how do you avoid the AI trap?
Swap tool-first thinking for a simple rhythm you can run every six weeks.

One page brief

One workflow. One owner. Baseline and a single target metric. Conversion, cycle time, or cost to serve.

Guardrails that fit risk

Automate where it is safe. Hand off where failure costs you. State the triggers.

Week six decision

Scale or stop. One slide with the before and after.

This keeps attention on outcomes and makes wins stick.

‍

Fit the process to your business

There is no one-size-fits-all. Treat the next six weeks like a fitting. Try the rhythm on one workflow. Walk with it. If the numbers hold and the steps feel natural, run with it. Then repeat on the next workflow.

Three moves you can make right now

1: Make content quote-ready and verifiable

If an LLM compressed your answer into one paragraph, would you back every word?

Do next week:

• Build a short proof pack for your top three objections. Pricing model, integrations, security questionnaires
• Write crisp answers with source links your CFO would accept
• Publish one public page per topic so humans and machines can find it
• Track a quote-readiness score. Green if the answer can be quoted as is

Why it pays: fewer stalls at the same stage and faster first responses from sales and support.

2: Cap bot autonomy where risk lives

Great bots route, enrich, and speed up simple work. Bad bots bluff.

Do in a day:

• Tag high-risk intents. Pricing, renewals, data, compliance, contracts
• Force a human handoff on those. State the trigger words
• Limit AI to lookups and drafts from a verified library
• Measure time to first response and error rate. Cut time without adding defects

Why it pays: faster help on safe queries with zero blow-ups on risky ones.

3: Run fewer, tighter experiments

Your team can only carry a handful of things with real focus.

Do this month:

• Put every AI pilot on one slide. Owner, metric, baseline, target, decision date
• Kill or pause anything with no owner or no target
• Move one winner into production and give it a name

Why it pays: momentum. Clear wins you can point to. Less noise.

Make AI work with people, not instead

The rhythm is simple. It fails when culture fights it. Teams win when strategists, writers, and planners are trained to direct AI, not just use it. That is the human in the loop.

Nobody chose this job to live in spreadsheets or reformat decks. AI should free people to think, create, and solve. Too many teams still use it to cut corners rather than raise the bar.

What good looks like

• AI embedded in live briefs, not side projects
• Teams trained to think with AI, not fear it
• Workflows designed for speed, clarity, and accuracy
• Clear governance so everyone is confident using it

How this reinforces the playbook

• Live briefs map to the One Page Brief. One owner. One metric. One decision date
• Thinking with AI matches Guardrails That Fit Risk. Humans keep calls on pricing, security, and legal
• Speed, clarity, accuracy align with Run Fewer, Tighter Experiments. Small scope. Weekly fixes. Scale what moves the number
• Governance is your citability checks, tagged risk intents, and handoffs. Safer answers. Fewer defects. Better trust
  ‍

Our approach

We help leadership teams move from AI-curious to AI-confident with practical, human-first frameworks:

• Audit where AI helps today and where it hurts
• Train teams to fold AI into daily workflows
• Track impact on quality, speed, and margin on one slide per cycle

Let’s wrap this up

You do not need more volume. You need proof.

• Make answers specific and verifiable so humans and AI trust them
• Cap bot autonomy where the stakes are high
• Run small, focused cycles and scale only what moves conversion, cycle time, or cost to serve

What I want you to take away

Cut the gimmicks. Back your people. Prove impact in small, steady steps that move real numbers.
The best client–agency relationships are built on challenge, not comfort.

Challenge the gimmicks. Choose proof. Then make it a habit.