1) How has Generative AI transformed traditional marketing workflows, and what specific challenges has it addressed in the industry?

This is still work in progress, obviously but we can see the early effects. Writing tasks have been the first to be handed over to AI, more in the administrative areas than the creative ones but that is gradually changing. I've seen translation work being heavily disrupted already, for example. We've been automating many admin and process workflows internally, showing clients and getting commissions to build equivalent solutions for them. It's marketing workflow for now but the principles apply to most areas of knowledge/office work. There are 3 benefits that the current generation of LLMs can give you once you build custom tools: admin work gets faster as more can be handled by the AI; processes (i.e. writing/responding to briefs in your company's style) can be sped up, made consistent and held to higher standards with AIs developing first drafts based on your rules and guidance; staff can be "levelled up" with AI bots that guide them through advanced thinking, techniques and skills that only the most experienced team members have otherwise.

2) Can you provide examples of successful marketing campaigns or strategies that have leveraged Generative AI? What were the key factors contributing to their success?

I have only seen examples of campaigns where AI has been used on a superficial basis at the moment - to do something visually cool for example. ML has been used with data for planning and strategy for years, so I'd consider this standard now. Maybe that's all we'll get. Human intelligence and creativity is what makes marketing campaigns great, after all. The current AI tools are making us faster and more efficient but not more creative.

3) As Generative AI evolves, what skills and competencies do you think marketers will need to stay ahead in the dynamic landscape of digital marketing?

In all jobs, knowing the fundamental skills and theory is vital. It's always been important, but now it's the best way to protect your job. Core skills like curiosity, a desire to learn, a passion for the job are more important than ever. There are lots of studies and analysis that show that about 25-40% of current jobs are going to go. To prepare for this do the above and/or diversify your skillset. Also, don't worry too much. Total employment should stay roughly the same in the long run and the new jobs created by and for AI could be pretty cool.

4) For enterprises considering the adoption of Generative AI, what are the key steps they should take to ensure a successful implementation?

The most important step in our projects is the knowledge and communication of existing processes. In handing over work to an AI, you first need to understand it and be able to describe it in perfect detail. All the flaws in your knowledge and process will be visible in the AI's work. Also, be patient. Like humans, AIs need time to learn, make mistakes and gain experience.

5) How do you foresee the future of Generative AI in marketing? What emerging trends could further shape the industry?

I think some areas like copywriting and media buying are getting totally transformed and the head count will drop in both. In many other areas, the output is less finite and more qualitative, so all the efficiency AI brings is getting reinvested into higher quality outcomes: higher conversion rates, more effective tactics, happier customers etc.

Question related to your session at the Generative AI for Marketing Summit

How can agencies rethink their value propositions as generative AI continues to disrupt the traditional agency model?

Agencies should look at their business model and what exactly clients are paying for. The first thing to do is audit your billed projects and work out what is vulnerable to change from AI and how. We scored all our line items from our scopes under 3 categories: AI-affected and now faster; AI-affected and now higher-quality; not AI-affected. If you bill by the hour, you can than calculate how much revenue is vulnerable. Note that the hourly billing business model isn't necessarily a problem. It's the outcome that you are billing for that is. Volume-based outcomes like a total amount of content pieces, ads, web pages are risky now. Goal-based outcomes like increasing market share, traffic levels, audience attitudes etc are not

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