Editorial & Advertiser Disclosure Global Banking And Finance Review is an independent publisher which offers News, information, Analysis, Opinion, Press Releases, Reviews, Research reports covering various economies, industries, products, services and companies. The content available on globalbankingandfinance.com is sourced by a mixture of different methods which is not limited to content produced and supplied by various staff writers, journalists, freelancers, individuals, organizations, companies, PR agencies Sponsored Posts etc. The information available on this website is purely for educational and informational purposes only. We cannot guarantee the accuracy or applicability of any of the information provided at globalbankingandfinance.com with respect to your individual or personal circumstances. Please seek professional advice from a qualified professional before making any financial decisions. Globalbankingandfinance.com also links to various third party websites and we cannot guarantee the accuracy or applicability of the information provided by third party websites. Links from various articles on our site to third party websites are a mixture of non-sponsored links and sponsored links. Only a very small fraction of the links which point to external websites are affiliate links. Some of the links which you may click on our website may link to various products and services from our partners who may compensate us if you buy a service or product or fill a form or install an app. This will not incur additional cost to you. A very few articles on our website are sponsored posts or paid advertorials. These are marked as sponsored posts at the bottom of each post. For avoidance of any doubts and to make it easier for you to differentiate sponsored or non-sponsored articles or links, you may consider all articles on our site or all links to external websites as sponsored . Please note that some of the services or products which we talk about carry a high level of risk and may not be suitable for everyone. These may be complex services or products and we request the readers to consider this purely from an educational standpoint. The information provided on this website is general in nature. Global Banking & Finance Review expressly disclaims any liability without any limitation which may arise directly or indirectly from the use of such information.

Getting real with AI: 5 areas for stakeholders to activate

By Jelena Stankovic, Content and Communication Lead at SAS

There is a lot of excitement about AI, but somehow the reality is not really living up to the hype. At the moment, we don’t see enough real results or use cases emerging, even though everyone agrees that there is huge potential. I polled some of our experts to find out why this might be happening and identified five critical barriers that need to be overcome for AI to move into the mainstream.

  •  You need a lot of data to build models

AI-based models probably need even more data than most because they need to learn for themselves. The explosion in the volume of data available from the Internet of Things, and particularly the increase in streaming data, should have made AI models far more ubiquitous. However, far too many organisations have not really caught up with this.

Joao Oliveira: “Streaming data is still an untapped resource for many, meaning that they are missing out on the power of analytics.”

Arturo Salazar: “Many have failed to appreciate that they may need to go hunting for new sources of data.”

Ivor Moan: “Data preparation is crucial for getting value from data. Skimp on the data preparation, and you will find that you cannot rely on your analytical results.”

In other words, organisations that do not pay enough attention to data, and especially data quality, will fail to capitalise on AI.

  •  Many models fail to move into production

Developing a model is relatively straightforward. The process often involves a number of different individuals and departments. Indeed, development and deployment are so different that they almost look like two separate life cycles, a bit like a salmon’s move from river to sea (and back again), according to James Ochai Brown.

Different skills are required, both project management-related and technological.

  • Users need to be able to understand insights from models

The best model in the world is only useful if it leads to action. That means that users have to be able to understand and interpret the outputs from the model to provide useful insights. Data visualisation is a crucial part of this process.

Data scientists, therefore, need to think about how they will demonstrate the outputs from their models to maximise the impact on viewers, for example, by asking themselves about the audience, and the message they wish to convey.

  •  The real benefit of AI is business model transformation – but that is a long-term project

According to Christer Bodell, any organisation can introduce a single AI-based project or model, and it will improve current business practices. Getting real benefits from digitalisation requires something more: a genuine change in philosophy and a commitment to innovation that is likely to result in business model transformation.

This requires a longer-term change in thinking, says Andreas Godde, and particularly a focus on how value is generated for customers.

  •  You need more users to increase use of AI – but they need to see others using it first

There is a book by Geoffrey Moore called Crossing the Chasm. It describes the difficulty of moving from “early adopters,” those who adopt a product because it is new and interesting, to the “early majority,” who will use products

because they are useful. The early majority need to see products being used by people like them, to solve real-world problems. AI faces a similar challenge – that at present, people do not see enough real-world examples of AI being used to solve problems.

Generate some of those, and particularly examples that show how AI can improve customer experience, and both companies and customers will be more prepared to accept AI and move across the chasm.