AI, BI or CI?

This article first appeared in Enterprise, The Edge Malaysia Weekly, on March 12, 2018 - March 18, 2018.

Cognitive and artificial intelligence solutions continue to proliferate across all industries, resulting in significant growth opportunities. > Daquila

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Most people have heard of AI (artificial intelligence) and BI (business intelligence), but few have heard of CI (customer intelligence). Some even call it cloud intelligence because so much customer data is now stored in the cloud. Is CI for real or just a figment of our imaginations?

Before we get to the numbers, let’s look at the definitions. AI is all about getting computers to perform tasks or processes that would be considered intelligent if done by humans. Does AI try to mimic human thought processes? No. A good AI system is just the best possible algorithm for solving a given problem.

In the case of an autonomous car, one of the many AI goals would be to avoid collisions and stay on course. It is not trying to process the data in the same way that a human brain does. After all, an autonomous car isn’t giving suggestions to a human driver — it is the one doing the driving.

BI involves analysing financial data (either historical or current) and uses modelling techniques to predict the performance and outcomes of business decisions. CI uses a combination of research tools to identify consumers that have the highest likelihood of loving — or hating — a brand or product. CI analytics may be derived by deploying tools such as CRM analysis, historical sales data, offline focus groups, research surveys and panel discussions.

Another aspect of cloud intelligence is doing AI or BI in the cloud, without hardware or infrastructure overheads. Given the rapid adoption of cloud computing by SMEs and large businesses worldwide, many companies now offer CI solutions. They include IBM (Cognos Analytics), Microsoft (Power BI), SAS (Visual Analytics), Amazon Web Services (Athena and Kinesis), Google (Dataproc and Big Query), Fusionex (Giant) and Zendesk (Zime).

 

Boom soon

How big is the AI market? Last year, the global market for such products and services was worth US$12 billion, up 59% from 2016. By 2021, the market is expected to exceed US$57.6 billion, according to the conservative estimates of International Data Corp (IDC). That is a compound annual growth rate (CAGR) of 50% from 2016 to 2021.

“Cognitive and artificial intelligence solutions continue to proliferate across all industries, resulting in significant growth opportunities,” says Marianne Daquila, IDC’s research manager for customer insights and analysis.

“Some of the use cases are very industry specific, such as diagnosis and treatment in healthcare. In others, they are common across multiple industries, such as automated customer service agents. The variety, application and nature of cognitive AI use cases is resulting in ubiquitous spend over the forecast period.”

Management consultancy McKinsey & Co notes that after decades of extravagant promises and frustrating disappointments, AI is finally starting to deliver real-life benefits to the early adopters, such as retail companies, utilities and vehicle manufacturers. Retailers on the digital frontier, for example, rely on AI-powered robots to run their warehouses and even to automatically order stock when inventories run low. Utilities use AI to forecast electricity demand while automakers harness the technology for self-driving cars.

“The entrepreneurial activity unleashed by these developments drew three times more investment in 2016 — between US$26 billion and US$39 billion — than it did three years earlier. Most of the investment in AI consists of internal R&D spending by large, cash-rich digital-native companies such as Amazon, Baidu and Google,” reports McKinsey.

Research firm Gartner estimates that global revenues in the BI and analytics software market may have reached US$18.3 billion last year, up a modest 7.3% over 2016. By end-2020, the market is likely to touch US$22.8 billion.

“Purchasing decisions continue to be influenced heavily by business executives and users who want more agility and the option for small personal and departmental deployments to prove success. Enterprise-friendly buying models have become more critical to successful deployments,” says Rita Sallam, vice-president of research at Gartner.

Who are the likely big spenders on AI and BI? The retail and banking sectors top the list, followed by manufacturing and healthcare. Their combined investments will represent up to 55% of all global spend on AI, says IDC.

“The retail industry invested about US$1.74 billion on AI last year. The BFSI (banking and financial services industries) likely invested another US$1.72 billion on cognitive systems and software. Between now and 2021, the biggest spenders will be the retail players,” it adds.

Why is this so? Because retailers will use intelligent process automation — including robotics and AI — to identify, optimise and automate labour-intensive and repetitive activities that are currently performed by humans. This will help reduce labour needs all the way from headquarters to distribution centres and stores. Many retailers are already expanding technology use to improve the in-store checkout processes. This may disrupt cashier jobs too.

“Retailers will be able to get labour savings by eliminating highly repetitive and transactional jobs, but will need to reinvest some of those savings in training associates who can enhance the customer experience. As such, most retailers will come to view AI as a way to augment customer experiences rather than just removing humans from every process,” says Robert Hetu, research director at Gartner.

 

Malaysia City Brain

AI will help transform industries in Malaysia as well, starting probably with retail. The country’s retail sales are set to grow 6% this year from 2017, compared with just 3.7% last year from 2016. Expectations of a general election and the resultant boom in business sentiment — as well as a stable currency — will fuel growth in retail spend.

“Malaysia’s retail industry is expected to maintain its growth potential, and government initiatives are expected to fuel the growth and accelerate IT spending for the retail industry. The young population, growing middle class and urbanisation are driving retail sales. This is expected to increase the online retail growth positively,” says Mike Ghasemi, research director at IDC Retail Insights for Asia-Pacific.

Another hotspot is manufacturing. While many industries perceive growing business value from the use of AI and BI, manufacturing is one that will receive a massive share of the business value opportunity. Factory automation will lead to cost savings while the removal of friction in value chains will increase revenue further — for example, in the optimisation of supply chains and go-to-market activities, according to analyst reports.

Early this year, Chinese giant Alibaba Group Holding Ltd deployed its smart city AI platform in Malaysia, the first such deployment outside China for the company. Called “Malaysia City Brain”, the initiative is a partnership between Alibaba, Malaysia Digital Economy Corp and Kuala Lumpur City Hall (DBKL). The programme uses AI software to analyse large volumes of data in an urban environment, captured via video, images and speech.

Alibaba first deployed the AI platform in Hangzhou, China. Malaysia will be the second. City Brain can construct a virtual digital city model and optimise it using machine learning tools to help make decisions pertaining to traffic management, road layout and planning, bus frequencies and routes, and the duration of time signals.

In due course, the Malaysia City Brain can connect with other urban management systems, including ambulance and emergency services, traffic controls and traffic lights management. The integrated platform will enable the city to analyse real-time data and optimise urban traffic flow, allowing optimal route management for emergency response vehicles such as ambulances and police vans. The aim is to enable start-ups, entrepreneurs, universities and research institutions to access the data to drive more insights and analytics.

 

Job jumble

The big question that is bothering everyone is: will AI take over human jobs? Not to worry, says Gartner. By 2020, AI will create more jobs than it eliminates. In real terms, AI will create 2.3 million new jobs by 2020 while eliminating 1.8 million redundant ones.

The number of jobs affected by AI will vary by industry. Healthcare, the public sector and education will continue to see growing job demand while manufacturing will be hit the hardest.

“Many significant innovations in the past were associated with a transition period of temporary job loss, followed by recovery and finally, business transformation. AI will likely follow this route,” says Svetlana Sicular, vice-president of research at Gartner.

“AI will improve the productivity of many jobs, eliminating millions of middle and low-level positions, but also creating millions more new positions of highly skilled management, and even the entry-level and low-skilled variety. Unfortunately, most calamitous warnings of job losses confuse AI with automation, which overshadows the greatest AI benefit — AI augmentation — which is a combination of human and AI, where each complements the other.”

What about BI and CI? Both will become components of AI as the ultimate aim is to benefit the customer. That is why about 50% of all spending on cognitive and AI technology will go to software and services, including cognitive applications and platforms, between now and 2021, says IDC.

On a geographical basis, the US will account for nearly 80% of global spending on cognitive and AI systems this year, and up to 75% by 2021. Europe, the Middle East and Asia (EMEA) is currently the second largest region, but strong growth from Asia-Pacific (including a 73.6% CAGR in Japan) will move it ahead of EMEA by 2021.

What is the prognosis for Malaysia? In a highly customer-centric world, the confluence of AI, BI and CI is the ideal equation. AI is ideally achieved when BI and CI — which are based on data points garnered from customer behaviour and interactions — are meshed with secondary economic, social and political data from the cloud to achieve prediction outcomes that are in the high 90% range. Malaysia has a golden chance to lead in this space in Asean going forward.