A Marketer’s Guide to Artificial Intelligence
Tuesday, August 6
Registration and Hot Breakfast
We’ll kick off the day with a nice breakfast so you’ll have energy for the day. You’ll also be provided with lunch and breaks throughout the day.
Artificial Intelligence Defined
- Science fiction vs. fact
- Voice recognition
- Natural language processing
- Computer vision
- Augmented reality
- Machine learning
Separating the Hype from the Possibilities
- Why now?
- General vs. narrow ai: when to roll your eyes/when to keep them wide open
- The myth of the AI-pocalypse
- Robots will not eat your job
- Scary pronouncements and the reasoning behind them
- Lack of explainability
- Bias in the data
- Bad actors
Intro to Marketing Analytics
- Analytics: A prerequisite to AI and ML
- What makes a great analyst?
EXERCISE: Marketing data literacy spectrum – Where is your organization today?
Machine Learning Explained - How ML is Different
- From programming to statistics to machine learning
- Examples of ML explained
- Decision trees become a random forrest
- Support vector machines
- Neural networks become deep learning
What ML is Good AT: Functional Proficiency
- Pattern matching
- Anomaly detection
What AI is Good FOR: Marketing
Where Machines Fail
- Statistics and logic are not reason and common sense
Wednesday, August 7
Breakfast will be waiting for you when you arrive for day two. Lunch and breaks will be provided throughout the day.
The New Importance of Data
- Need for large amounts of data
- Need for clean data
- Need to understand data streams
On-boarding AI - How to bring AI and ML into Your Organization
- Goal Identification
- Task prioritization
- Choosing useful data sets
- Working with data scientists
- Buy vs. build
- Change management and expectation setting
EXERCISE: The AI maturity model – Where do you stand?
Keeping Your Job - Uniquely Human Skills & Strengths
- Perfecting the smell test
- The power of experience
- The need for creativity
- The power of collaboration
- Soft skills become paramount
EXERCISE – Identifying the best place to start
- What is your top, corporate goal?
- Which is your most agile marketing task/ function/ team?
- Who in your company is most likely to support experimentation?
- Who in your org has budgetary discretion?
- Where/from whom do they get their input?
- Which repetitive tasks are best for pilot projects?
- What is your next step?
A Look Over the Horizon - The Weird Future Right Around the Corner
- Training an ecosystem of bots
- Systems that negotiate with systems
- Brand building becomes even more crucial