Preparing Marketing and AI Teams for 2027
“Prepare for a year in which people ask technology to prove its usefulness and institutions to prove their trustworthiness.”
Marketers and AI practitioners should prepare for a year in which technological capability grows alongside economic pressure and uncertainty about whom to trust. The opportunity lies in making customers’ lives easier, improving how organisations operate and demonstrating that promises are supported by dependable practice.
Three historical perspectives help explain this combination. Giambattista Vico examined how societies develop and how shared obligations can weaken as private interests dominate. Nikolai Kondratiev proposed long waves of economic expansion and decline. James Joyce drew on Vico in Finnegans Wake, exploring recurring human patterns through a family’s experiences.
These ideas offer ways to interpret change. They provide no reliable timetable for 2027, and Kondratiev’s cycles remain disputed. Read alongside current evidence, however, they suggest four developments worth preparing for: uneven prosperity, deeper AI adoption, stronger demand for security and belonging, and greater commercial value attached to demonstrable trustworthiness.
Expect economic growth to coexist with customer pressure. The IMF’s October 2026 forecast projects global growth of 3.4% in 2027, while the OECD’s September forecast puts it at 3.0%. Both identify substantial risks. An expanding economy can still contain households postponing purchases and businesses tightening budgets. Begin with customer research that identifies where those pressures affect decisions. Review lost enquiries, cancellation reasons, sales conversations and repeat purchasing. Ask which customers need lower initial costs, which need greater certainty, and which will pay more for dependable service. Update segmentation using these findings.
Translate the evidence into specific offers. A consultancy might introduce a clearly scoped diagnostic with a fixed fee, a subscription business might improve its pause options. Explain total costs and expected outcomes, and test whether these changes improve conversion without creating unsustainable servicing costs.
AI practitioners can help analyse feedback and identify changes in demand, with people checking whether the patterns make sense. Combine this work with scenario planning: agree what changes in acquisition costs, margins or retention would trigger a budget review. This gives teams an agreed response when conditions shift. Keep a modest testing budget available, with clear spending limits, so emerging opportunities can be explored quickly without disrupting essential activity or committing the organisation to costs it cannot sustain.
Prepare for AI to become part of everyday operations. The ONS reported that 30% of UK businesses used AI in September 2026. Adoption creates opportunities to redesign work, alongside pressure to demonstrate that investment produces useful results. The likely pace will vary considerably between organisations and sectors.
Select one recurring workflow with a clear problem, such as preparing campaign reports, classifying customer enquiries or checking product information. Establish its current cost, completion time and error rate. Give an accountable owner responsibility for the pilot and define what success must look like before implementation begins. Measure the whole process. Include licences, integration, training, human review and correction costs. For a reporting assistant, check factual accuracy and whether managers make better decisions using its output. A faster draft creates value when the completed task also meets the required standard.
Involve employees in redesigning their work and explain how responsibilities may change. Define which actions require approval, what information the system can access, and when it must hand over to a person. Agree how to pause the system if performance deteriorates. Review results before expanding its use.
Anticipate stronger demand for security and belonging. Vico’s concern about weakening shared obligations offers a useful interpretation of fragmented public debate. People facing uncertainty may place greater value on organisations that are understandable, accessible and consistent. This is a planning hypothesis that teams should test with their own audiences.
For marketers, begin with the moments when customers feel exposed: making an unfamiliar purchase, sharing personal information, experiencing a delay or seeking a refund. Explain what happens next, who is responsible and how to get help. Ensure the actual service can deliver the reassurance in the message. Create opportunities for useful participation through customer panels, practical learning sessions and communities with a clear purpose. Make space for disagreement and show what changes because people contributed. Track unresolved concerns and participation over time to understand whether those relationships are becoming stronger.
AI practitioners should support this confidence through clear interfaces and accessible human escalation. Explain when customers are interacting with automation and what it can reliably handle. Give people an effective route to challenge an incorrect answer or decision, with someone responsible for resolving the problem.
Treat trustworthiness as something customers can verify. Edelman’s 2026 UK report found that 76% of respondents were unwilling or hesitant to trust people with specified differences in outlook or background. Based on late-2025 fieldwork, it provides context for understanding the difficulty of building trust across unfamiliar relationships.
Audit the organisation’s most important claims. For each promise, record the supporting evidence, its limitations, an owner and a review date. Check that testimonials are genuine, performance claims reflect relevant conditions, and sustainability statements have adequate support. Correct claims when products, services or evidence change.
Apply the same discipline to AI. Evaluate outputs against representative examples, including difficult cases, before deployment. Record significant failures and use them to improve the system. Track complaint resolution, repeat purchasing and customer understanding alongside marketing results. These measures reveal whether the experience supports the organisation’s promises.
So you can use the next 90 days to make progress. In the next month, establish customer and operational baselines and audit major claims. In the next, test one offer improvement and one AI workflow. In the third, assess the results, involve customers and employees in the review, and decide what to expand, amend or stop. Bring marketing, operations and AI owners together monthly to review this evidence. Keep agreed measures visible and record the decisions they prompt, so learning carries into the next campaign and deployment.
Joyce’s recurring human dramas remind us that new technology arrives among familiar hopes, fears and ambitions. Preparing for 2027 means attending to those experiences while improving delivery. Organisations that help people make informed choices and reliably fulfil their commitments will have a stronger basis for earning confidence, whatever the next economic turn brings.
For 2027, I would put the greatest weight on four developments:
- Economic growth will continue, with considerable dissatisfaction beneath the headline figures. The IMF’s October forecast projects 3.4% global growth in 2027; the OECD’s September forecast projects 3.0%. Both identify substantial risks. Continued growth can coexist with stretched household budgets, struggling sectors and governments with limited spending room.
- AI will increasingly change how organisations operate, with greater scrutiny of its financial returns. My expectation is more redesign of tasks, services and staffing, alongside consolidation among suppliers. The ONS reported that 30% of UK businesses used AI in September 2026. Among AI-using businesses with at least ten employees, 6% reported reducing headcount because of it. That supports an outlook of uneven organisational change; the scale of future displacement remains uncertain.
- Demand for security, competence and belonging will strengthen. Persistent uncertainty makes promises of protection and dependable leadership attractive. That demand could support effective institutional reform, stronger local relationships or more concentrated political authority. The direction will depend on choices and circumstances. In the World Economic Forum’s September survey, 77% of chief economists expected greater geopolitical and economic fragmentation over the following year.
- Demonstrable trustworthiness will become more commercially valuable. My inference is that organisations offering verifiable claims, reliable service and clear accountability will gain an advantage as people become more selective about whom they believe. Edelman’s findings on trust in familiar relationships support that possibility, although they do not guarantee a particular commercial outcome.
The biggest potential change to this outlook would be an escalation in conflict or energy disruption, or a sharp reassessment of AI investment. Conversely, easing tensions and measurable productivity gains could produce a stronger year. Both possibilities feature in the current economic forecasts. So decide what you can do personally, to prepare for a year in which people ask technology to prove its usefulness and institutions to prove their trustworthiness. Great opportunities await.
Sources
Internet Encyclopedia of Philosophy: Giambattista Vico.
Kondratiev: The Long Waves in Economic Life, reproduced in the Narrative Science anthology.
Northwestern University Press: James Joyce and the Philosophers at Finnegans Wake.
Technological Forecasting and Social Change: Controversial curves of the economy.
IMF: World Economic Outlook, October 2026.
OECD: Economic Outlook, September 2026.
ONS: Business insights, 8 October 2026.
Edelman: 2026 UK Trust Barometer.
