It is indeed an AI arms race. Those who master AI more shall reap more prosperity, because they shall boost their GDP at an unprecedented rate. Laggard businesses and nations shall find themselves on the wrong side of a widening competitiveness gap.
Here we will illustrate AI benefits by listing some compelling tangible use cases where AI technology is already generating economic value.
Two Broad Categories
We will divide our top use cases into two broad categories where value can be created:
1- Operational efficiencies (Op$)
Operational efficiency is basically the ability to do more with less. There are so many processes in every organization that can be re-imagined by including more data analytics and smarter software. More so if we embed IoT sensors and possibly some robotics. An easy to visualize example is to think about how agriculture was automated in the previous century so it generated a lot more crop using a lot less human resources. AI has the potential to produce a similar leap in productivity.
2- Customer experience (CEX)
Customer experience has many facets but it boils down to how easy, fast, convenient and/or enjoyable your products or services are from a user perspective at every touch point in the customer journey. CEX became the main competitive differentiator in the digital age (think Amazon). What the internet and e-commerce enabled in terms of more convenient shopping experience was a quantum leap from traditional stores. With AI and “Journey Science” we can now achieve another substantial leap for CEX where customer advocacy of your company (NPS) rises and customer acquisition and retention costs decline.
Verticals in Focus
There is a large number of use cases for Big Data and AI that apply to each industry. Here are some use cases for Telecom and Smart City context to use as inspiration for your own case.
Customer Journey management is a game-changing use case of big data and AI with applications in every industry from Retail to Telecom.
Traditional Data Warehouse at telecom service providers typically processes and analyzes only a small percentage of available customer data. Telecom service providers have adopted big data analytics as a strategic competency for many reasons:
- to gain insights into the customer journey
- to improve customer experience and loyalty
- to offset downward pressure on their revenues
- to prepare for 5G networks and IoT
Customer Journey management is a key use case of big data and AI with applications in every industry from Retail to Telecom.nue declines (Op$). The urgency has risen by another order of magnitude with the imminent introduction of IoT services.
2- Smart City
One driver for Smart City adoption is population growth and migration towards cities that is resulting in pressure on the environment and city resources. So the advances in digital technologies (including IoT) became an inspiration for re-imagining urban life in order to reduce governance costs (Op$) and provide a better lifestyle for the citizen (CEX).
Major cities in the EMEA region have launched ambitious smart city initiatives. These are major undertakings in terms of scope and scale, far exceeding what large corporations have to contend with. Smart cities encompass many government agencies and include public/private partnerships so realizing them requires architecting a complex “System of Systems”. AI will play a major role in increasing the level of process automation (Op$) and enable more innovative “Smart” services (CEX).
What if insurance companies can find ways to assess risks much more accurately by leveraging big data analytics and AI? Detecting fraud early? Providing evidence to support a denial? Providing metered car insurance based on actual usage and driving style? Many leading insurers started on this track years ago. And there are success stories and the experiments are getting extended and refined. From car insurance to health insurance, there are note-worthy use cases that will lead to a revamp of the insurance business model.
4- And many more
Below is a list of 100 start-ups using or selling AI to challenge incumbents in a variety of industries in 2020. There are likely 1,000s more globally getting ready to launch. And we are just in the early stages of this transformative wave, with predictions that the growth will be exponential over time.
Incumbents can and should defend their leadership positions by launching digital transformation initiatives that run deep into their organization. Everything in the old order should be open to questions and scrutiny, including questioning what business you are really in, what other lines of business you can launch in parallel, and the adequacy of your current business model. Otherwise one of the 1,000s of AI-infused startups (or a transformed incumbent) may soon show up in your rear-view mirror.