AI and marketing: what should CMOs be thinking about?
In a recent article, I wrote about the importance of protecting authenticity and originality in an AI world.
I remain convinced that we need to think before we reach for the tool. But that does not mean I am sceptical about AI. Used well, it can give marketing teams access to more insight, greater capacity and faster execution than many could previously afford.
For CMOs and marketing leaders, however, the question is not simply: How can my team use AI?
The more important questions are:
Where can AI create meaningful commercial advantage?
Which marketing capabilities will become more important?
How should the function work differently?
What must remain under human control?
How do we introduce AI without compromising trust, quality or originality?
This is not simply a technology decision. It is a leadership, operating-model and capability question.
The opportunity is much bigger than content creation
Much of the conversation about AI in marketing focuses on producing articles, emails and social posts more quickly.
That may deliver an immediate productivity gain, but it is one of the least strategically interesting applications.
The greater opportunity is to use AI to help marketing understand the market more deeply, make better decisions, improve commercial focus and respond more quickly to change.
At a CMO level, AI has the potential to strengthen five important areas:
Market and customer intelligence
Strategy and positioning
Marketing productivity and capability
Sales and marketing alignment
Measurement and decision-making
The objective should not be to generate more marketing activity. It should be to improve the quality, relevance and commercial contribution of that activity.
1. Building a stronger market-intelligence capability
One of the most valuable applications of AI is its ability to monitor and analyse more information than a marketing team could reasonably process manually.
This might include:
Policy and regulatory developments
Procurement activity
Competitor positioning
Customer announcements
Funding decisions
Search behaviour
Market commentary
Emerging customer concerns
For organisations selling into the public sector or regulated markets, this is particularly important. A change in policy, funding, leadership or procurement can alter the market opportunity, the buying process and the messages that will resonate.
The CMO’s role is not to receive a longer news summary. It is to turn external developments into commercial intelligence.
That means asking:
What could this change mean for our market?
Which customers are likely to be affected?
Does it create a new opportunity or risk?
Should we change our proposition, content or sales activity?
Where should we act now, monitor developments or avoid unnecessary distraction?
AI can accelerate the research and surface connections. The CMO must provide the commercial context and decide what warrants action.
2. Making customer insight more useful
Most organisations already possess a considerable amount of customer intelligence. The problem is that it is often fragmented across CRM records, proposals, meeting notes, surveys, support enquiries, emails and the knowledge held by individual employees.
AI can help identify recurring themes across this information:
The problems customers describe most often
The language they use to explain those problems
The objections that slow down decisions
The benefits that matter to different stakeholders
The points at which opportunities lose momentum
The questions sales and delivery teams are repeatedly asked
For a CMO, this creates an opportunity to build a more systematic customer-insight capability.
It can help the organisation move away from marketing what it wants to sell and towards addressing what customers are actually trying to achieve.
It can also help identify differences between audiences. An operational leader, technology director, procurement professional and chief executive may all be involved in the same decision, but they will assess the proposition through very different lenses.
AI can help expose those differences. Human experience is still needed to interpret them and decide how the organisation should respond.
Customer and commercially sensitive information must, of course, only be used in appropriately secure and approved systems.
3. Strengthening strategy, positioning and propositions
AI can be an effective thinking partner during strategy and proposition development.
It can help a marketing leader:
Test the clarity of an argument
Compare different positioning options
Identify assumptions that require evidence
Explore how competitors may respond
Examine a proposition from different stakeholder perspectives
Find inconsistencies between corporate messaging and customer needs
Challenge whether a claimed differentiator is genuinely distinctive
This is particularly useful because teams can become too close to their own organisation, products and language.
However, AI cannot decide what makes a business meaningfully different. That has to come from the product, the customer experience, the organisation’s expertise, the evidence and the choices its leadership makes.
If the proposition is weak, AI may disguise the problem with polished language. It cannot create a sustainable competitive advantage where none exists.
The CMO remains responsible for making choices: who the organisation is for, what it wants to be known for and what it will not try to be.
4. Redesigning how the marketing function works
AI gives CMOs an opportunity to reconsider how work moves through the marketing team.
It can help with:
Research and summarisation
Campaign planning
First drafts and content adaptation
Meeting and interview analysis
Account research
Reporting and performance commentary
Workflow administration
Repetitive production tasks
For smaller marketing teams, this can provide access to capabilities and capacity that would previously have required additional people or external support.
But introducing AI is not simply about asking the existing team to produce more.
CMOs need to decide:
Which work should be accelerated?
Which work could be automated safely?
Where should the time saved be reinvested?
What skills will the team need?
Which activities no longer add enough value?
Where must human review be mandatory?
If AI creates capacity, the best use of that capacity may be deeper customer engagement, stronger strategic thinking, better collaboration with sales or more time spent developing original ideas.
Success should not be measured by the number of additional assets produced.
5. Creating better alignment between marketing and sales
AI can help close some of the gaps between marketing and sales.
It can bring together account research, previous interactions, campaign engagement and wider market developments to create a more informed view of an organisation or opportunity.
It can also help teams:
Identify accounts showing meaningful interest
Understand which issues are attracting engagement
Prepare for customer meetings
Tailor messages for different decision-makers
Summarise conversations and commitments
Recommend relevant follow-up actions
Identify where an opportunity may be stalling
The aim should not be indiscriminate automation or a larger volume of generic sales messages.
It should be more relevant, timely and informed human contact.
At a leadership level, the opportunity is to create a shared intelligence and planning process rather than allowing marketing and sales to use AI in isolation.
6. Improving measurement and decision-making
Marketing teams often spend significant time assembling reports that explain what happened but do not provide enough insight into why it happened or what should happen next.
AI can help interrogate performance more quickly. It can identify changes, compare campaigns, analyse patterns across audiences and suggest questions that deserve further investigation.
A useful CMO-level report should help answer:
What is changing?
Why might it be changing?
What is contributing to pipeline or customer engagement?
Where are we investing without sufficient evidence of impact?
What should we stop, continue or change?
What decision needs to be made?
AI may identify a pattern or possible explanation, but it cannot automatically understand every commercial, organisational or market factor behind it.
The CMO must ensure that recommendations are supported by reliable data and tested against the wider context.
AI also creates leadership responsibilities
The advantages are considerable, but so are the risks.
These include:
Inaccurate or invented information
Generic and repetitive content
Bias within data or recommendations
Confidentiality and data-protection failures
Unsubstantiated claims
Copyright and ownership concerns
Loss of a distinctive brand voice
Over-automation of customer communication
Increased activity without improved commercial outcomes
Marketing leaders need a clear framework for the responsible use of AI.
That should establish:
Which tools are approved
What information can and cannot be entered
Where human review is required
How facts, sources and claims will be checked
How the organisation will protect its voice and intellectual property
When the use of AI should be disclosed
Who remains accountable for the final output
This cannot be delegated entirely to IT. AI affects the brand, customer experience, reputation and quality of the organisation’s external communication. The CMO therefore has an important role in its governance.
What remains distinctly human?
AI can help marketing teams:
Research
Analyse
Organise
Compare
Challenge
Draft
Adapt
Automate appropriate tasks
People must remain responsible for:
Setting the strategy
Understanding the context
Exercising judgement
Checking the evidence
Making ethical decisions
Creating original ideas
Building trusted relationships
Taking accountability for decisions
The strongest model is not human or artificial intelligence. It is human expertise supported by technology and grounded in good information.
Where should a CMO begin?
There is no need to introduce AI across the whole marketing function at once.
A better starting point is to identify a small number of commercially important problems.
For example:
We cannot monitor our market consistently.
Valuable customer insight is dispersed across the organisation.
Our proposition is not understood by different decision-makers.
Marketing and sales do not share a complete view of target accounts.
The team spends too much time assembling reports.
Content production is absorbing time that should be spent on higher-value work.
Choose one problem. Define the outcome. Establish the appropriate safeguards. Keep a person accountable for the work. Then assess whether AI has genuinely improved the quality, speed or commercial value of the result.
AI can help marketing teams do more. At CMO level, its greater value lies in helping the organisation understand more, decide more confidently and focus its resources where they can make the greatest difference.
The opportunity is not to replace marketing judgement. It is to make better use of it.
This article was developed with AI assistance. The perspective, examples, editorial judgement and final conclusions are my own.
