Full Screen

AI Considerations

More Free Lessons in

Data and Analytics View All →

Get cutting-edge digital marketing skills, know-how and strategy

This micro lesson is from one of our globally recognized digital marketing courses.

Start a FREE Course Preview Start a FREE Course Preview
Global Authority

The Global Authority

12 years delivering excellence


245,000+ Members

Join a global community


Associate Certification

Globally recognised


Membership Included

Toolkits, content & more

Digital Marketing - Study Notes:

AI-related concerns

AI has given rise to some real social concerns:

  • Employment issues is one of the key concerns, particularly when machines start to replace humans’ jobs across a variety of industries and fields. So how do we make sure that people have sufficient jobs? Of course, AI, or automation, doesn’t render us all unemployed. Indeed, we need to think about other areas of employment that AI will struggle to fill.
  • Inequality is a concern, because there will be obvious winners and losers in this regard. We need to think about how high-intensity capital versus lower intensity capital is measured and considered to reduce inequalities. In some future predictions, the rich will get very rich and the poor will be made poorer as their jobs and modes of income are replaced by AI processes.
  • Nothing is perfect, so robotic errors are inevitable in an AI environment. How can we anticipate these problems and develop solutions for them?
  • It is important to consider software security. Recognize the issues around software security and then engage with AI to solve these problems.

Economic impacts

The economic impacts of AI include the following:

  • AI enables faster decision-making. This in turn enables us to respond or adapt more efficiently.
  • AI also results in lower costs because of reduced decision inputs and manual inputs.
  • AI facilitates better job allocation. You can steer people away from manual tasks and have machines take care of those duties.
  • AI creates greater scale for you. In other words, you can upscale your operation in a much more robust way, and with a lot less variability.

Technological singularity

The technological singularity is the hypothesis that the invention of AI could abruptly trigger runaway technological growth, resulting in unimaginable changes to human civilization. Fundamentally, this could possibly shift the way that humans operate, we live, the way that the economic model works, the way that we have employability, humanity, and jobs.


Some of the benefits of AI and Machine Learning include:

  • Low error rates when applied correctly
  • It reduces human effort in repetitive tasks
  • 24/7 application


The limitations include:

  • It requires Supervision
  • There's limited creativity and scope of improvement with experience
  • They are still unable to replace humans
Back to Top
Jack Preston

Jack Preston is a Data Scientist working within marketing analytics, with a particular focus on strategic customer loyalty. Jack has experience working in both small-scale startups and large corporates, including dunnhumby and Notonthehighstreet. He also holds an MSc in Business Analytics from UCL where he graduated with distinction.


Jack Preston
Skills Expert

This short course covers the principles of analytics and demonstrates techniques and useful tools that you can use to develop and refine your knowledge of data analytics.

You will learn:

  • The fundamentals of data, collecting data, and processing data, including best practices, techniques, and challenges
  • The principles of web analytics, the benefits and limitations of Google Analytics, terminology for reporting, and the legalities around consent and data privacy
  • The concepts of Big Data, the processes around data, including mining, scraping, cleansing, and de-duping, and the various languages and programs for testing your data
  • The importance of AI, Machine Learning, analysis types, the value of testing hypotheses, and forecasting based on the data available
  • How best to report and present data findings to management and the different tools available to you

Approximate learning time: 3 hours