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AI-ML,

AI – Ready or not here it comes

Friendly AI

Everybody talks about Artificial Intelligence but no one understands it. When we hear the term AI, we think Terminator, Blade Runner, Ex Machina, 2001 Space Odyssey and many other filmes that have introduced the public to the concept of AI. If we were to base our opinions of AI on the films we have watched, then AI is nothing but smart computers that want to kills us all!

This will be the subject of today’s post (no, it is not about smart computers killing us all), what is AI, how can organisations use it effectively and some of the common challenges to avoid.

What is AI?

So what is AI? AI is a bit difficult to define artificial intelligence as definitions and expectations keep changing with time. This is referred to as AI Effect.

For the last thirty years, AI has experienced repeated cycles of over promising and under delivering on business value. This led to what was called AI Winter where no one considered AI, let alone invested in it. Ever since then, AI had a negative stigma attached to it.

AI today, includes a few technologies, such as Machine Learning, Deep Learning, Computer Vision, Robotics, Natural Language Processing, Computer Vision and list keeps growing.

Deja Vu

Yet it feels like a Deja Vu, with AI emerging again. So what has changed today to make AI a viable investment?

A few things have changed. Today we have massive powerful compute made affordable by public cloud services. Also, major players such as Google, Microsoft, Amazon, IBM are investing heavily in AI R&D. Data Science has become a popular major in universities, producing bigger numbers of qualified talent. Also, the great success of virtual assistance such as Alexa, Siri, Google, contributed to new-found appreciation of AI.

Many of the digitally native, born in the cloud, new start-ups are utilising AI to provide a richer user experience. Their great success in grabbing market share from incumbents has made most businesses sit up and pay attention to the resurrected AI.

However, many CIOs are not sure where to apply AI in the business to gain the most value. After all, AI requires significant investment and measuring ROI becomes a requirement for building a business case.

Areas of AI Adoption

Areas that are seeing great success with AI adoption today are:

Sales, Marketing, Security & fraud detection, HR, Medical and Digital Workplace amongst a few others.

I will use sales & marketing as an example as they tend to show high business value, due to direct impact on revenue. In sales, AI can identify deals in pipeline that are likely to close, help price deals competitively and improve pipeline forecast significantly.

In marketing, AI has been very effective in improving recommendation engines that lead to substantial increases in upsell and cross sell for many online shopping outlets. Also, AI has been very effective in recognising customers that are likely to leave, which results in high retention rate.

The above are only a few use cases of many successful AI adoptions. Although AI has proven its potential to be of great value, yet many businesses fail to recognise that value.

Common Challenges

The following are common reasons behind the disappointing results of AI adoption:

  • Lack of defined scope. Many organisations are quick to surf the wave of AI adoption without validated scope and defined business outcomes.
  • Shortage in skilled personnel. The demand by far exceed supply of talent, which has created a bottleneck holding back many AI adoption initiatives.
  • No clear defined AI adoption strategy connected to corporate strategy.
  • No clean data available for the AI initiative. Data is the fuel that drives AI and without it, AI initiatives are destined to stall.

Artificial Intelligence vs Amazing Innovations

Many organisations are adopting AI for quick wins, such as automation of processes and applications with cost optimisation as a benefit. However, these quick wins are tactical in nature. The strategic approach, is to identify use cases that will have a deeper long lasting impact. For example,  identifying use cases to use AI to gain business insight to help with strategic decision making or use AI to innovate business interaction with customers, for a richer customer experience. These strategic use cases will turn AI from Artificial Intelligence to Amazing Innovation.

AI is a very disruptive technology and organisations that are not the disruptor will end up being the disruptee.

I hope you have found the post informative and thank you for reading and sharing.

 

Regards,

Nick

 

AIMachine_Learning

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3 Comments

Mike

April 8, 2020

Thank you for an easy to read post. We are trying to figure out where and how to apply AI in our organization.

Reply

Axelle

April 9, 2020

Very nice blog 🙂

Merci

Reply

Lovan

April 18, 2020

How do you determin which strategic use cases to persue?

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Recent Comments

  • Virtual Tarzan on Cloud Migration – Where to start?
  • Dan on Cloud Migration – Where to start?
  • Virtual Tarzan on How to Maximise Benefits from Multi-Cloud Adoption
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  • Virtual Tarzan on How to Maximise Benefits from Multi-Cloud Adoption

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