Digital Marketing in the Age of AI Disruption (Part 2)
In Part 1 of this series, we discussed the parallels between the current hype surrounding artificial intelligence (AI)–especially with ChatGPT and Bard with three other transformative technological changes that molded human history. These included:
Digital Marketing in the Age of AI Disruption (Part 1)
We’ve all seen the headlines, artificial intelligence (AI) is either a) going to mark the end of humanity, or b) make the world a better place. With all the hype surrounding generative AI and ChatGPT,
Mastering B2B Marketing
The digital economy is now more customer-centric than ever. In business-to-business (B2B) marketing, we have moved from advertising, press releases, inbound sales, and promotions to more customer-centric and experiential marketing. Organizations now need to deeply understand what B2B buying committees want across an ever increasing number of channels.
The Art of The AI KPI
With the current economic uncertainty that surrounds us, Chief Data and Analytics Officers are under increasing pressure to track the business impact of data, analytics, and AI initiatives on business outcomes. In most organizations, that leads to talk of key performance indicators (KPIs).
Busting AI Myths: Getting Started with AI
Have you started using artificial intelligence (AI) and machine learning (ML) in your analytics initiatives? What kind of results are you seeing?
Crossing the AI Chasm
The analytics chasm fundamentally boils down to one thing: a lack of analytics capacity within your organization.
Four Steps to Remove AI Waste
When you think about decision making in the context of those steps, you realize that the information value of data is perishable, and it decays with time. If you remove the analytics waste from your decision-making process, you can become much more competitive.
Why Organizations Need to Double Down on Analytics to Drive Innovation
Dynamic and uncertain marketing conditions have created new opportunities, but organizations will need to prioritize their analytics investments to seize them.
Beyond the Hype, Towards a Pragmatic Definition of Artificial Intelligence
Given the historical context and a high-level definition of how AI is applied, how can we create a practical definition of AI? In my mind, the definition of AI is quite simple. Artificial Intelligence = Data + Analytics + Automation