Why Experience Matters More in the Age of AI

AI can draft a campaign platform, generate fifty headlines and summarise a year of customer commentary in the time it takes to make coffee. It can also answer the wrong question fluently, miss the importance of a local detail and recommend an action that looks sensible until it reaches the public.

The difference is not speed. It is judgement.

Experience matters more in the age of AI because options are becoming abundant. The scarce professional skill is deciding which option fits the evidence, the organisation, the audience and the moment. In brand, marketing, public relations and corporate communications, that decision can affect money, trust and reputation. It needs a person who understands the context and is prepared to answer for the result.

Used well, AI is an extraordinary professional tool. Its value depends on knowing when to use it, question it or set its answer aside.

When answers become cheap, judgement becomes valuable

Generative AI can produce research summaries, concepts, copy variations and translations at a speed no communications team could match manually. The gains are real, but they do not remove the work around the output.

Someone must frame the problem, provide the relevant context, test the evidence, recognise what is missing and decide whether the proposed action should proceed. That is judgement: making a defensible decision when the information is incomplete, and the consequences are not entirely predictable.

Experience supplies reference points. A seasoned communicator has seen an apparently harmless phrase interpreted in an unexpected way, a minor issue become serious because the response was slow, and a restrained decision prove wiser than a more dramatic one. Those patterns do not provide automatic answers, but they help a professional recognise what deserves attention.

In my work with multinational organisations and leadership teams, I have found that the most consequential question is often not, “What can we produce?” It is, “What are we prepared to stand behind?” AI can expand the options. Experience helps narrow them responsibly.

Experience is earned, not accumulated

Experience should not become a defence of hierarchy. Time served is not expertise, and repetition is not learning.

Daniel Kahneman and Gary Klein's work on professional intuition offers a useful distinction. They concluded that reliable intuitive skill is most likely to develop in environments containing learnable patterns, where practitioners receive meaningful feedback. Confidence in one's experience is not evidence that the judgement is correct.

Experience becomes valuable when exposure is combined with reflection and renewal: listening to audiences, observing consequences, testing assumptions, learning from failure and keeping knowledge current. AI makes that distinction more visible. It can expose the difference between genuine expertise and seniority protected by habit.

The experienced professional is therefore not the person who claims to have seen everything. It is the person who knows what previous experience can illuminate, where it may mislead and what still needs to be verified.

AI has a jagged frontier

Research does not show that AI is uniformly brilliant or uniformly unreliable. Its capabilities are uneven.

A field experiment involving 758 consultants at Boston Consulting Group, published in Organisation Science in 2026, found that AI improved performance on tasks within its capability frontier. On a task outside that frontier, however, consultants using AI performed worse.

The difficulty is that two tasks which look similarly demanding may sit on opposite sides of that boundary. Even highly qualified professionals can fail to notice when the tool is leading them away from the right answer.

Other research shows how effectively AI can transfer competence in a bounded environment. A 2025 Quarterly Journal of Economics study covering 5,172 customer-support agents found that AI assistance increased productivity by 15% on average, with the largest gains among less-experienced and lower-skilled workers.

Experience should not protect routine work or exclude capable newcomers. AI can raise the baseline of execution. But brand positioning, reputation and public commitments involve ambiguity, novelty and competing interests. When the script no longer fits, judgement carries the work.

Communications experience provides context that data cannot

A model can process a brand book, previous campaigns and media coverage. It may still miss the reason employees distrust the official narrative, the promise operations cannot yet deliver or the political history attached to an apparently neutral phrase.

Context often lives in relationships, institutional memory and details that were never written down. This is particularly important across Romania, Central and Eastern Europe, the Middle East and North Africa, where my work has repeatedly required global ideas to be assessed against local language, regulation, culture and public expectation.

Literal localisation is not cultural judgement. An experienced communicator knows when an idea can travel, when it must be adapted and when it should be abandoned.

Experience also helps reveal second-order effects. A product claim may improve response rates today while creating a credibility problem tomorrow. A public position may reassure one audience and alarm employees, regulators, partners or investors. This is why reputation management and crisis communication cannot be reduced to the optimisation of one metric.

Across financial services, energy, manufacturing, technology, pharmaceuticals, retail and FMCG, the immediate communications task may differ. The professional responsibility is consistent: understand who else may be affected, anticipate how the decision may travel and make sure the organisation can support what it says.

Taste becomes more important when competence is easy to imitate

Generative AI can produce polished material that resembles what is already circulating. That makes acceptable execution cheaper and distinctiveness harder to protect.

A 2024 Science Advances experiment involving 293 UK participants found that access to AI-generated ideas improved evaluations of individual short stories, particularly for less creative writers, while making the stories more similar to one another. Short fiction is not advertising, so the finding should not be stretched beyond its scope. It does, however, illustrate a risk that brand teams should recognise: individual outputs may improve while the overall body of work becomes less distinctive.

Taste is not mystical. It is informed discrimination, developed through attention to language, culture, customers, competitors, results and craft. It allows a professional to explain why an attractive option is generic, why a clever line is wrong for the organisation or why the least dramatic response may earn the most trust.

This is also where genuine thought leadership separates itself from automated content production. Authority does not come from publishing more often. It comes from having knowledge, a defensible point of view and something useful to add.

Relationships and accountability remain human

Public relations depends on trust between people. A difficult conversation with a chief executive, an honest exchange with a journalist or a warning to a client cannot be reduced to text generation. Timing, credibility and courage matter as much as the words.

Board-level counsel and high-stakes communications have taught me that the technically strongest answer is not always the advice a leader can act on. The adviser must understand the pressures around the decision, explain the consequences clearly and challenge without turning the discussion into a performance.

That judgement is central to media relations and corporate communication. AI can help prepare the analysis or improve the draft. It cannot preserve a difficult relationship, accept responsibility for the recommendation or stand behind the advice when the outcome is challenged.

Romania can build good habits before scale arrives

Eurostat reported that 20% of EU enterprises with at least ten employees used AI technologies in 2025, compared with 5.2% in Romania. The gap is substantial, but it should not be read only as a failure to catch up.

Romanian organisations have an opportunity to establish sound practice before weak habits become embedded. They can define appropriate use cases, protect sensitive information, verify outputs, assign clear responsibility and retain experienced review wherever reputational stakes are high.

The objective should be better work, not simply more activity produced by fewer people. Adoption without judgement does not close a capability gap. It automates it.

The EU AI Act provides a useful foundation. Article 4 requires providers and deployers to support an appropriate level of AI literacy, taking account of people's technical knowledge, experience, education, training and the context of use. For high-risk systems, Article 14 requires effective human oversight and explicitly addresses the danger of over-relying on automated output.

These provisions reinforce a durable management principle: responsible use depends on people who understand both the system and the situation.

Efficiency can create experience debt

Researching, monitoring, drafting and preparing briefings are not merely junior tasks. They are also how early-career professionals learn. They see why a senior colleague changes a line, hear how a stakeholder responds and discover what happened after publication.

If junior practitioners only polish machine output, they may become faster without becoming wiser. The organisation captures efficiency today by consuming tomorrow's learning opportunities. That is experience debt.

The European Communication Monitor 2024/25, based on interviews with 30 chief communication officers drawn from Europe's 300 largest companies, found that more than 55% used AI often or always for analytics and insights. The report also emphasised coaching, reflection and intergenerational knowledge transfer, including reverse mentoring.

That combination matters. Younger practitioners can help senior colleagues understand new tools and behaviours. Experienced colleagues can explain why a decision was made, what happened next and which warning signs are easy to miss. Judgement should develop in both directions.

A practical model for experience-led AI use

The level of human control should match the consequences of the task. Six practices turn that principle into day-to-day discipline:

Classify work by consequence. Use AI more freely for low-risk tasks such as transcription, clustering and first-pass summaries. Require experienced review for positioning, regulated claims, public commitments, crisis response and culturally sensitive issues.

Form a view before consulting the tool. Ask the responsible professional to define the problem, initial hypothesis and decision criteria first. This reduces the risk that a fluent output frames the entire discussion.

Demand evidence and expose uncertainty. Verify sources, distinguish fact from inference and record what remains unknown. An unsupported AI answer is a proposition to investigate, not a conclusion to publish.

Name the human decision owner. Every consequential output needs a person who can explain the reasoning, approve the choice and accept responsibility for the result.

Protect apprenticeship. Let junior practitioners attempt core work, meet stakeholders and observe consequences. Review their reasoning, not only the finished draft.

Create feedback loops. Record important decisions and review outcomes after a campaign or issue. Compare what the team expected with what happened so that experience becomes learning rather than anecdote.

These practices require more than prompt fluency. A sound AI strategy for communications also covers data handling, intellectual property, bias, disclosure, model limitations, verification and organisational risk boundaries.

Communicators do not need to become machine-learning engineers. They do need enough AI literacy to understand what an output can support, which information should not be entered, when specialist advice is required and why the final decision remains human.

Experience is the advantage, provided it keeps learning

AI will make acceptable output cheaper and faster. It will not make sound judgement automatic. The organisations most at risk are those that publish the wrong promise, follow the wrong signal or mistake a plausible answer for a responsible decision.

Experience provides an advantage because it connects knowledge with consequence. It helps a communicator recognise patterns without becoming trapped by them, exercise taste without hiding behind preference and make a decision without pretending uncertainty has disappeared.

The strongest teams will use AI to widen the possibilities and experience to narrow them wisely. In the age of AI, the premium will not belong to the person who can produce the most. It will belong to the person whose judgement others can trust.

Lighthouse PR helps leaders and communications teams turn experience, evidence and strategic judgement into brand decisions that stand up in public.

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About the Author

Ana Maria Gardiner is a senior communications executive, board-level adviser and founder of Lighthouse PR. She has extensive experience providing strategic counsel to multinational organisations and leadership teams across corporate reputation, public relations, marketing communications, crisis management and high-stakes communications.

During her career, Ana Maria has led and implemented communications strategies for organisations including JPMorgan, Coca-Cola, ExxonMobil, Siemens Energy, HEINEKEN, Carrefour, Lexus, Franklin Templeton, BNP Paribas, Sungrow, XTB, Bitget, EssilorLuxottica and Pfizer. Her work spans the Middle East, North Africa and Central and Eastern Europe across a broad range of industries and business environments.

She advises senior executives and boards on reputation management, strategic positioning, communications risk and responses to sensitive situations and crises. Ana Maria holds a bachelor's degree in Political Science and a master's degree in European Affairs.

About Lighthouse PR

Lighthouse PR is an independent public relations and strategic communications consultancy headquartered in Bucharest, working with organisations across Romania, Central Europe and South-Eastern Europe. Its senior-led services include corporate communications, media relations, reputation management, crisis preparedness and response, stakeholder and investor communications, social media and influencer management, B2B communications, risk assessments, business continuity planning, corporate events, media buying, and SEO and website design.

Lighthouse PR holds ISO 9001 and ISO 27001 certifications and is the exclusive representative for Romania and the Republic of Moldova of Eurocom Worldwide and Crisis Communication Network Europe.

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