Apply AI to your marketing: AI creativity in social media, content, branding or product development and solve marketing problems with confidence using AI
Leading industries are now using GenAI for 22.8% of marketing activities.*
To help you keep up, we have one of the most practical courses in AI on the market, spread over three (3) weeks with 1:1 live coaching to allow for application to your organisation and work. Understand how to use AI as a problem-solving and quality improvement tool, using proven methods to identify, define, and drive impactful projects.
Learn the fundamentals of generative and analytical AI, apply quality in your AI using the DMAIC (Define, Measure, Analyse, Improve, Control) framework to problem-solve marketing problems.
Learn from the combined experience and expertise of certified marketing and quality practitioners, University data science master’s lecturers and data scientists from global marketing agencies. All from London, UK, a global centre for the creative industries sector.
Who Should Attend
All marketing managers wanting to understand the impact of generative AI and general AI on marketing or start AI R&D projects and benefit from R&D tax benefits*
Marketing managers that want to start to practice and use generative AI in their role to get productivities of 63-65%** and keep up with the market.
This course will particularly benefit: product marketing, brand, content marketing, digital marketing managers, partnerships / alliance, market research, social media, content marketing, account based marketing, search engine optimisation (SEO), paid media, owned media, marketing comms.
Course Outline
Week 1: Learn the fundamentals of AI
1:1 coaching: your AI context (outside course hours)
- Generative AI, non-generative AI, data science, and traditional statistical improvement methods in the context of marketing creativity and problem-solving
- Common off-the-shelf AI tools for marketing
- AI marketing use cases in creativity and problem-solving
- Possible practical marketing challenges AI could solve in your organisation.
Week 2: Apply AI to your work
1:1 coaching: iterating your AI to your work context (outside course hours)
- Deciding which AI marketing use case is best for you
- Hands-on practice: experiment with methods for identifying, scoring, and prioritising potential AI projects addressing practical challenges
- The proven DMAIC framework for AI-based problem-solving
- Case study of AI-driven solutions to complex marketing problems using DMAIC
- Identifying solutions using generative AI. Prompt engineering techniques for problem-solving and creativity
- Breakout working with peers to apply AI with DMAIC to solve the marketing problem you identified in your work.
Week 3: Get impact from your AI
1:1 coaching: sustaining your AI (outside course hours)
- How to sustain your AI project using DMAIC to maximise impact and minimise risks of AI
- How to use quality methods to define your AI effort as an AI R&D project and benefit from tax incentives
- Hands-on practice: experiment with AI and DMAIC tools to measure and control your AI project for sustained impact
- Breakout: progress your AI project with a clear action back when back at work.
Learning Outcomes
- Understood generative, and non-generative AI and data science in the context of marketing creativity and marketing challenges.
- Practised using AI tools for creativity and problem-solving
- Learned how to use proven, structured problem-solving frameworks to maximise the impact and reduce the risks of AI with confidence.
- Defined a practical marketing challenge from your work and applied AI to it together with marketing peers.
- Use quality tools to support your AI project as an R&D project for tax incentives.
- Learned prompt engineering techniques, quality tools and how to use them in marketing creativity and problem-solving with impact.
This course includes
- 7 hours of total learning
- Learning over 3 weeks for maximum application to your work
- 2.5 hours of practical work and coaching
- AI toolkit with tools, templates and methods
- 3 1:1 live coaching sessions with experts over 3 weeks
Possibility of integrating the course in an AI R&D project providing SMEs 43.5% of the costs back via R&D Tax Incentives
*The CMO Survey, Fall 2024.
Facilitators
John Paul Danaee
John Paul Danaee is a British-Australian, co-founder and director of equitably.ai and CEO of AI First Trading (an equitably.ai joint venture) in London, UK.
He is a Chartered Marketer, a Fellow of the Australian Marketing Institute and the Chartered Institute of Marketing in the UK and an alumnus of the University of Sydney and UNSW, Australia. He is a Chartered Quality Professional and Lean Six Sigma certified Black Belt.
John Paul is a frequent writer and speaker on AI including the UK Department for Business & Trade, Bayes Business School (London), the Federation of Small Business and the Investment Association. He is passionate about getting impact from AI, recently published a feature in Quality World on it, organises the executive AI roundtable in London focused ROI from AI, chairs the AI working group at the Chartered Quality Insitute and working with UN’s AI for Good Learning Coalition.
John Paul has 30+ years of experience in marketing, performance improvement, and automation across technology, media, manufacturing, professional services, investment management and banking sectors in the UK, Australia, the US, Europe, and internationally in major corporations such as HSBC and tech startups including equitably.ai in roles including, marketing strategy, product management, partnerships, sales, and account management.
Dr Tillman Weyde
Dr Tillman Weyde is Director Co-founder, Artificial Intelligence & Data Science at equitably.ai in London, UK.
In his role as Director of AI, he manages data scientists working at equitably.ai, captures and translates leading-edge AI research from Universities, research centres, and partner collaborations to solve business problems through AI.
He has published 150+ peer-reviewed papers, won research grants from national and international institutions and companies, has been awarded several awards for research and developed and award-winning software.
Tillman is a Reader at the Department of Computer Science, School of Science and Technology at City, University of London. He is a member of the Research Centre for Adaptive Computing and Machine Learning and of the Data Science Institute at City, University of London.
Dr Aneesh Banerjee
Dr Banerjee is a Reader in Management and presently leads the Technology and Innovation Management subject group at Bayes Business School, City, University of London.
His award-winning research focuses on various types of technology adoption – from ERP to Automation and AI – in several industries such as high-tech, software, healthcare, fintech, cultural & creative industries.
His most recent research focuses on the perceptions and values associated with AI tools among different stakeholders within complex systems.
Pedagogically, as the founding Course Director of the online Global MBA, he led the academic development of the degree as well as courses such as ‘Competitive Edge with Digital Technologies’ and ‘Leading AI and Industry 4.0’. He teaches on the MBA, Executive MBA, as well as custom Executive Education programmes, specialising in topics on Digital Strategy. His pedagogical contributions have been recognised with the University Chancellor’s Award. Before joining academia, Dr Banerjee worked in technology consulting with leading global firms.
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