{"id":5049,"date":"2026-08-09T02:53:12","date_gmt":"2026-08-08T23:53:12","guid":{"rendered":"https:\/\/ivitskiy.com\/blog\/board-london-2025\/"},"modified":"2026-08-09T02:53:12","modified_gmt":"2026-08-08T23:53:12","slug":"board-london-2025","status":"publish","type":"post","link":"https:\/\/ivitskiy.com\/blog\/en\/board-london-2025\/","title":{"rendered":"The AI Era in Advertising and Marketing: Igor Ivitskiy at Board London 2025"},"content":{"rendered":"\n
In short:<\/strong> At Board London, Igor Ivitskiy argued that AI does not create business judgement on its own: it amplifies the context, standards and feedback a company gives it. He showed three places where that leverage matters most: management decisions, customer understanding, and marketing in a search market increasingly shaped by generative systems. In his year-long visibility experiment, about 90% of roughly 70 friends who repeated a narrow expert query in ChatGPT were shown Igor as the recommendation. The practical conclusion was not to replace people, but to give them better decision support while keeping a human responsible for the outcome.<\/div>\n\n\n\n

Board took place in London, United Kingdom, on October 17, 2025, as an in-person business talk followed by a live discussion. The speaker was Igor Ivitskiy<\/a>, an entrepreneur and former mathematical modelling researcher who applies systems thinking to advertising and marketing.<\/p>\n\n\n\n

The talk, \u201cThe AI Era in Advertising and Marketing: How an Entrepreneur Can Build 5x Leverage\u201d<\/strong>, connected AI-assisted management, synthetic customer perspectives, generative-search visibility and the changing economics of paid media. Its common thread was that the old craft of keyword research for Google Ads<\/a> now sits inside a wider problem: supplying algorithms with useful context and trustworthy business signals.<\/p>\n\n\n\n

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\u224890%<\/div>\n
of roughly 70 friends who repeated a narrow expert query in ChatGPT were shown Igor as the recommendation<\/div>\n<\/div>\n
Source: Board London talk, Igor Ivitskiy, October 17, 2025.<\/div>\n\n\n\n

AI multiplies context, not judgement<\/h2>\n\n\n\n
\"Owner
Owner surrounded by ads, content, analytics and AI<\/figcaption><\/figure>\n\n\n\n

Igor framed AI as a mirror. A generic instruction tends to return generic management advice because the model has no reason to understand the company\u2019s positioning, audience, constraints or definition of a good result. The same model becomes more useful when it works with a coherent business context and receives corrections from someone accountable for the decision.<\/p>\n\n\n\n

This explains why apparently similar AI projects can produce opposite reactions. One company sees a stream of plausible but irrelevant text; another sees a useful second opinion before committing money or time. The difference is less about finding a magical prompt and more about whether the system has a clear role, reliable reference material and a feedback loop.<\/p>\n\n\n\n

The principle also sets a boundary. AI can widen the field of options, compare evidence and preserve organisational memory, but a person still defines the standard and owns the consequence. That is especially important when a decision affects customers, money, health, law or reputation.<\/p>\n\n\n\n

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1<\/span>Decision architecture<\/strong>
Use business context to challenge operational and strategic choices before resources are committed.<\/div>\n
2<\/span>Customer understanding<\/strong>
Turn research, feedback and first-party data into sharper questions about what customers value or reject.<\/div>\n
3<\/span>Discovery and advertising<\/strong>
Prepare for a market where generative answers, search pages and ad algorithms increasingly shape the same journey.<\/div>\n<\/div>\n
Source: three-part structure of Igor Ivitskiy\u2019s Board London talk.<\/div>\n\n\n\n

My rule for AI-assisted decisions<\/strong><\/p>

I treat an AI system much as I treat broad match in Google Ads<\/a>: it can expand the field I can see, but it still needs a clear business goal, good signals and a human who knows what must be rejected.<\/p><\/section>\n\n\n\n

This way of thinking is also relevant to training: the durable skill is not memorising one interface, but learning how to frame a business problem, test an answer and keep responsibility with the decision-maker. The school\u2019s programmes develop that same analytical discipline in advertising and marketing.<\/p>\n\n\n\n\n\n\n\n

Key insights<\/h2>\n\n\n\n