AI as a Partner in Promotional Marketing

Debate motion: “AI should be seen as a partner to the promotional marketing industry, not a disrupter.”

Debate location: Committee Room 14, House of Commons, London SW1A 0AA, United Kingdom

Debate date: Tuesday, November 25, 2025, 5:00–7:00pm GMT

On 25 November 2025, marketers will gather in Committee Room 14 at the House of Commons to debate the motion: “AI should be seen as a partner to the promotional marketing industry, not a disrupter.” The event is chaired by Lord Black of Brentwood, with Oliver Yonchev and Dan Hirons speaking for the motion, and Dr Amr Al Khateeb and Mays Elansari speaking against it.

Before the debate, I wanted to capture my own reflections on the motion. I've written these ahead of hearing either side, to help shape any comments I might make on the day.

In this article, I look at what "AI as a partner" means in practical terms for UK promotional campaigns. If you run campaigns, work in brand, or advise clients, you will find examples, risks to watch for and simple starting points for using AI without losing control.

Core benefits of AI in promotional marketing

AI is most powerful in promotional marketing when it acts as a partner. It helps teams gain a competitive edge, move faster, target campaigns more precisely, reduce waste and unlock more space for strategic and creative thinking. Used well, the technology improves the experience for people on the receiving end of your promotions: more relevant offers, fewer irrelevant messages and smoother journeys.

Behind the scenes, modern platforms combine machine learning with historical data and live customer interactions. They help brands define clearer marketing goals, understand customer needs and track customer behavior and feedback in one place. This turns raw numbers into relevant content and experiences that deliver a genuine competitive advantage for the business and feel more useful for the audience.

How AI speeds up planning and rollout

AI dramatically speeds up promotional campaign work. Tasks that once took weeks of research, planning and manual setup can now be done in hours, sometimes minutes.

Instead of starting from a blank page, smart tools can:

• Analyse historic performance and predict which campaign concepts and channels are most likely to work.
• Turn a basic brief into draft campaign structures, audiences and creative ideas.
• Generate a full content calendar with suggested topics, formats and posting times.

Practical time-saving examples

Practical examples include:

• Scanning market trends and competitor activity in real time.
• Auto-drafting campaign briefs, creative options and message variations while streamlining marketing tasks.
• Building first-pass content schedules and asset versions for different channels.
• Rapidly shaping proposals and decks for client or internal feedback, shortening review cycles.

The result is faster campaigns without asking teams to work longer hours.

How AI improves ad targeting and personalisation

People increasingly expect marketing that feels relevant to them, not just to a broad demographic segment. The future of AI helps deliver that level of personalised promotion at scale.

By analysing large volumes of behavioural and transactional data, these systems can spot patterns humans would miss: what people browse, what they buy, how often they engage and where they are in the journey. This allows marketers to move beyond simple age or location targeting and build segments based on real interests and actions.

Behaviour-based targeting lets brands respond to what people actually do, not just who they are. For example, an e-commerce brand can identify visitors who viewed a product but did not purchase and automatically trigger a tailored follow-up such as a complimentary item, a how-to guide or a time-limited offer. Natural language processing can scan reviews and social posts to understand what customers actually care about, feeding back into messaging and offers.

From demographics to behaviour

Done well, ad targeting makes marketing feel less like interruption and more like a relevant conversation. The same recommendation logic we see on platforms like Netflix or Amazon is now available across promotional channels.

The benefits of AI-driven personalisation include:

• Showing dynamic content that adapts in real time to a person’s behaviour.
• Running highly focused ad sets for micro-segments with shared interests or intents.
• Serving product recommendations and incentives tailored to each individual.
• Shaping every stage of the journey around that person’s context.

Using AI to boost accuracy and compliance

Manual campaign work is vulnerable to human error: a wrong price in an offer, a broken link in an email or a message sent to the wrong audience. In promotional marketing, these slip-ups do not just hurt performance; they can damage trust and, in some cases, break regulations.

Specialised tools reduce this risk by acting as an additional quality and compliance layer. They can:

• Scan copy and creative for off-brand language, insensitive phrasing or risky claims.
• Check that mandatory terms, conditions and disclosures are included and correct.
• Flag potential issues with audience selection, such as targeting the wrong age group.

For brands operating across multiple markets, automation can help keep messaging consistent and aligned with central guidelines, even when many campaigns are live at once.

Brand safety tools supporting regulation and compliance

On the regulatory side, these systems can support adherence to data privacy and advertising rules. Platforms can be configured to enforce consent requirements, respect local regulations and log decisions for audit purposes. As adoption grows, these checks will become a standard part of responsible promotional marketing.

The outcome is simple: fewer costly mistakes, stronger brand protection and greater confidence that technology-powered promotions are safe as well as effective.

AI-driven operational efficiency and smarter spend

When AI is treated as a partner in promotional marketing, it becomes a powerful engine for operational efficiency. It helps teams do more with the same budget, or achieve the same results with less. External research reinforces this. A PwC and ANA study found that "leading marketers" deliver 79% greater total shareholder value than their peers, and that companies using AI for more than speed and cost-cutting can unlock over twice the marketing-driven profitability. 

Instead of manually combing through reports, marketers can use dashboards that surface what matters in real time: which channels are underperforming, which audiences are converting and where spend is being wasted.

Live optimisation in practice

Automation can then recommend, or even carry out, adjustments such as:

• Shifting budget from low-performing ads to those driving stronger results.
• Pausing segments with poor engagement before they consume more spend.
• Testing new creative variants where performance has plateaued.

AI makes continuous, live optimisation possible across campaigns. Systems now continually tune the mix, ensuring each pound of promotional spend works harder. This level of optimisation was almost impossible when everything was managed by hand.

The payoff is twofold: reduced media waste and more time back for the team. Rather than firefighting, marketers can invest that time in better propositions, partnerships and long-term growth initiatives.

How AI strengthens creativity by removing repetitive work

Used well, AI strengthens creativity and the human touch. Many people fear the opposite, but the evidence shows that when AI takes on repetitive, operational tasks, creative teams gain time to think and experiment. McKinsey's 2025 survey agrees, finding that 64% of organisations say AI is enabling innovation, not just efficiency gains.

Routine activities such as data pulls, basic reporting, content formatting and simple A/B variants are essential but draining. Generative tools can handle first drafts of email copy, social posts or headline options, giving creatives something to react to rather than a blank screen.

Keeping humans in control of the idea

In this partner model:

• Automation suggests ideas, angles and variations; humans decide what is on-brand and compelling to take it to the next level.
• Tools handle scheduling and distribution; humans shape the story and the offer.
• Systems test dozens of small creative tweaks; humans focus on the big concepts and narratives.
• The result is a better use of human talent. Marketers spend less time on administrative campaign management and more time understanding their audience, building distinctive concepts and nurturing relationships with customers, partners and internal stakeholders.
• Technology takes care of the “how we ship this efficiently”; people stay in charge of “what we should say, and why it matters.” That is what it means for AI to be a true partner to promotional marketing, not a disrupter.

Use-cases and practical applications

Data-driven marketing is most valuable when you see it in day-to-day campaigns, not as a theory. The real impact shows up in how teams run and optimise real promotions. Across the UK, businesses of all sizes are already using intelligent marketing tools as a partner in promotional marketing. These platforms help teams turn data into shared, customer insight that everyone can act on. That insight drives stronger customer engagement, higher response rates and more accountable results.

AI now supports every step of the promotional customer journey. It helps with campaign planning, audience segmentation, creative content generation, channel selection, real-time optimisation and brand safety and compliance checks. The real-world examples below show that these tools are not far-off dreams. They are already built into the way marketing teams work today.

Where UK brands start

Real-world examples: AI in UK promotional campaigns

Marketing leaders across the UK are using technology-enabled tools to get better results from the same, or even smaller, promotional budgets. By using smart systems to understand customer data, they can deliver more relevant messages at the right time and in the right place.

Pazza Pasta: personalised tips in Whatsapp

Pazza Pasta is a food delivery brand that promotes offers through WhatsApp. According to Braze, they added intelligent tips to its messages, using recommendations based on what each customer likes and has ordered before. As a result, the number of people buying went up by six times compared to the email-only campaigns.

OneRoof: personalised property newsletters and higher engagement

OneRoof is a property platform that relies heavily on email to drive traffic back to its site. It introduced intelligent decisioning to personalise its newsletters, using real-time customer data and on-site search behaviour to decide which properties and tips to show each subscriber. Each email became a local, useful, property update instead of a generic blast. This personalisation delivered a 218% jump in clicks on property listings and more people taking action on the site.

fedora: smarter timing, channel choice and loyalty

Online food delivery service foodora used machine-led insight to understand customer behaviour to refine their promotional messages. By predicting the best time, channel and audience for each offer, the platform helped them send promotions when people where most likely to care. This shift in timing and targeting led to higher conversion rates, more loyal customers and more revenue, with messaging feeling more relevant and less intrusive.

Together, these examples show how the right AI adoption can have a big impact on campaign performance. The marketers still set the strategy, understand the brand and define what "good" looks like, but they now use better tools to get it done faster and more effectively.

AI-powered campaign planning and segmentation

Using evidence instead of guesswork

Smarter audience segmentation

AI transforms audience segmentation from broad demographic buckets into precise, behaviour-based groups. Instead of relying on age, gender or location, teams can build smaller, more detailed segments based on real consumer behaviour and intent.

For example, a system can identify a group of people who have recently looked at a specific product, respond well to weekend offers and prefer app notifications over email. Getting this precise with data at scale was not realistic before these tools became widely available.

Today, this smarter way of planning and segmentation runs inside many marketing automation platforms. They do more than pick the right groups; they also suggest which channels, messages and timings are best for reaching those people. The human planner oversees the process, selects from recommendations and builds a supported campaign from the start.

AI creative content generation and A/B testing

Generative technology is now a major help when it comes to creating and testing marketing content, particularly in terms of customer segmentation. It makes it easy to generate many different versions of promotional messages quickly, which allows teams to run structured A/B testing at scale.

Copywriters no longer need to spend hours producing just a few variants of an ad, landing page or email. With automated support, there can be a dozen or more new options in just a few minutes. The copywriter’s role shifts towards editing, strengthening and ensuring that the content matches the brand voice, legal rules and campaign goals.

Testing and learning at scale

High-volume, multi-channel campaigns benefit most from this test-and-learn approach. When you publish across social media, email, in-app messages and website banners, AI-generated variants make structured testing much easier. When content creation tools handle the first draft, creative teams gain time to look at performance data, refine the message and plan future campaigns.

Common uses include:

• Generating different headlines for one article or landing page to see which attracts more clicks.
• Making tailored ad copy for each social media platform, based on tone and format.
• Drafting personalised email marketing messages for different customer segments or life stages.
• Creating several versions of a landing page to increase sign-ups, redemptions or purchases.

Brand safety and compliance checking

Automating checks for every asset

Systems can scan every piece of marketing content, including emails, ads, landing pages, push notifications and even user-generated content. They check it against brand guidelines and highlight anything that seems off. With natural language processing and sentiment analysis, platforms can spot risky wording, negative tone or messages that do not fit the brand’s personality. This is particularly important when managing social media channels, where conversations move quickly.

For regulatory compliance, you can configure platforms to check that all promotions meet advertising standards and data protection laws. They can flag issues with how prices are shown, whether terms and conditions are clear, whether consent rules are respected and whether sensitive audience targeting is being used correctly. When you build these checks into your marketing strategy, your promotions are more likely to be effective, fair and within the law.

The impact of agentic systems on workflow and results

Agentic systems act as a connection layer between marketing platforms and channels, coordinating work that used to be manual. This shift is already changing how marketing teams work and what they can achieve. They help organise tasks, coordinate actions and keep many moving parts running by themselves, within guardrails set by humans. By handling several steps in a row, they help campaigns move smoothly from planning to execution to optimisation.

They take on some of the work a project manager or campaign manager would do, but in a digital form. This means marketing teams do not have to spend as much time on repetitive, low-value tasks such as manual reporting, list building or simple follow-ups. Instead, they can work in a more agile way and put more effort into bigger strategic plans, creative thinking and stakeholder management.

From simple automation to AI-orchestrated workflows

Examples of agentic marketing in action

Agentic marketing goes beyond simply making tasks automatic. It helps to run whole workflows across different tools and platforms, guided by a clear goal. These systems can be set up with an objective, for example to hit a target cost per acquisition or to improve customer retention, and then work on their own within predefined rules to move closer to that goal. They provide actionable insights, much like generative AI technologies, as they go, so teams can see what is happening and why.

Imagine a marketing team rolling out a new promotional campaign. An agentic system can monitor performance in the first hours and days across all channels and segments. If the system sees that results are weak for a certain audience, it might automatically reduce spend for that segment, test a new creative variant and increase budget for a better-performing group. It can do all this without someone stepping in for every small change, while still logging each decision for review.

Typical agentic marketing goals

Other practical uses include:

• Budget optimisation, where the agent observes campaign performance and shifts budget between channels, bids and creatives when it spots patterns in conversion behaviour.
• Reputation management, where the agent watches social media and review sites for negative comments, pauses certain ads during a crisis and alerts PR and customer service with a summary of concerns.
• Lead nurturing, where the agent tracks how new leads interact with content, sends tailored email sequences, creates tasks in the CRM and attaches summaries of interests so follow-up calls are more relevant.

Improving collaboration across teams with AI support

AI support, especially when delivered through agentic systems, is also a powerful way to improve collaboration between marketing teams and enhance customer relationships. In many organisations, groups such as data analytics, creative, campaign management and customer service do not always share information easily. This can slow down work and create frustration.

Intelligent platforms can act as a central connection point, linking these groups and passing useful information between them. For example, a system might analyse customer service chats powered by AI chatbots and find that customers often ask the same question about a promotion or product feature. It can then create a task or brief for the content team, suggesting an FAQ article or explainer video. Once the content is published, the platform can alert the digital marketing team so they can promote it, and send the link back to customer service so agents can share it with customers.

Sharing insight across teams

Integrating AI tools for promotional marketing without losing control

Bringing AI tools into your promotional marketing workflow does not mean you have to give up control. With a careful, step-by-step plan for adoption, you can gain the benefits of automation while keeping strong human oversight. The goal is to use AI to support smart, informed decisions based on user behavior, not to let new tools act entirely on their own.

The safest way to adopt AI is to start small. Choose one simple, low-risk task that AI marketing could help with, such as generating different subject lines for an email campaign or alternative versions of a social media post. Treat this as your first test project and monitor how the technology works, what it does well and where it falls short. As your team builds confidence and skills, you can expand AI use to more parts of your marketing strategy over time.

Choosing transparent, collaborative platforms is critical. Look for tools that provide manual approval steps, clear logs of automated decisions and the ability for people to override or adjust suggestions. Defined goals and strong guardrails let the system operate within a framework you set.

By taking this approach, AI acts as a supportive layer for campaign management, not a replacement for human judgement.

Conclusion

To sum up, using AI as part of your promotional marketing is now a key step in getting things done faster, with more accuracy and greater creativity. When you use these tools wisely, your business can plan campaigns more effectively, anticipate future trends, target the right people, optimise spend and follow the rules more easily. The promotional marketing industry has always embraced new technology, and this is simply the next logical step in that journey.

Even though some people worry that AI might bring big changes, it can make your marketing efforts stronger when used in the right way. It adds to what people can do instead of taking their place. Bringing together human insight and machine capability leads to new ideas, clearer strategies, better customer experiences and better results. Treating AI as a partner in promotional marketing helps brands rise above the noise and create campaigns that genuinely resonate.

If you want to explore what these tools could do for your own promotional campaigns, the safest route is to start with a small pilot, clear goals and strong controls, then build out from there.

Frequently asked questions

What are the benefits of AI as a partner in marketing?

The main benefits of using AI as a partner in marketing include:

• Speed, through faster planning, testing and optimisation.
• Personalisation, with messages and promotions that better match each person’s needs and interests.
• Performance, via improved conversion rates and a stronger return on marketing investment.
• Focus, as marketers spend less time on manual tasks and more time on strategy, ideas and brand building.

What tools help promotional campaigns?

Several types of tools can be useful for promotional campaigns:

• Marketing automation platforms such as HubSpot or Braze, which help with campaign management and journey orchestration.
• Predictive analytics tools, which estimate how customers are likely to act and which channels or offers will perform best.
• Generative systems for creating copy and content for emails, ads, landing pages and social posts.
• Chatbots that answer customer questions quickly and collect useful data about common needs and issues.
• Agentic platforms that coordinate workflows across multiple systems in support of a set goal.

How does AI enhance ad targeting and personalisation in promotions?

AI enhances ad targeting and personalisation by analysing vast amounts of data and large sets of customer data. It looks at what people browse, buy and interact with, as well as how often and when they return. This gives a richer view of each customer and supports more effective audience segmentation.

Instead of relying only on basic details such as age or location, marketers can build smaller, high-intent groups based on real behaviour, such as recent website activity, engagement with previous campaigns or interest in certain product categories, allowing them to better understand their target audience. With this insight, teams can choose what sort of content, promotion or message each segment is likely to respond to and when to show it.

What challenges should businesses consider when partnering with AI for marketing?

There are several important challenges to consider:

• Bias and fairness, because models can copy unfair patterns from historic data.
• Data protection and privacy, including compliance with laws such as GDPR.
• Skills and culture, since teams need time and training to become confident users of new tools.
• Control and accountability, so humans stay in charge of key decisions and can explain how outcomes were reached.

By addressing these issues early, businesses can make sure AI strengthens their promotional marketing instead of creating new risks.