- Uttam Mishra
How to build a business case for AI
The mid-1950s boasted the launch of artificial intelligence, with the presentation of the first artificial intelligence program, Logic Theorist (1)(2).
In the following 65 years, as computing power has continued to increase, we have seen huge growth in the capabilities of AI and its value in processing the increasing volumes of data defining our digital age.
Despite the potential value in large datasets, the sheer magnitude of data has meant that most organisations are progressively struggling to uncover all the possible insights using the power of their human workforce alone, when looking to make informed decisions and consider many scenarios.
The ability for AI, in tandem with computing power, to work alongside employees and uncover the value of data, has allowed it to permeate into all areas of modern life, from online shopping to healthcare, to the benefit of companies that adopt it rapidly.
The value extracted by AI will soon render adoption a necessity for companies seeking to remain competitive in an increasingly digital market.
Why an AI initiative is necessary today
History has shown that fortune favours the brave, and, on top of that, there is a prevalent winner-takes-it-all phenomenon when it comes to technology.
In the last 20 years alone, technology has shaped our lives and society beyond recognition, with the rapid rise of relatively new companies like Netflix, Amazon and Uber. In order to retain relevance in the market, companies must be willing to quickly adopt digital advances as new technology raises the competitive bar.
Amazon:
From its creation, Amazon has been defined by its attitude to rapid digital adoption, which has allowed it to dominate the market in recent years.
Soon after it was founded in 1994 (4), Amazon was quick to embrace the opportunities of selling online, with the launch of its online bookshop in 1995, and as a key player in the rise of E-books (3).
The hunt for cheaper prices online, and the promise of a more enjoyable and practical shopping experience has contributed to an innovation in the way we shop, led and encouraged by businesses like Amazon, who benefited as a result.
In the 1990s, book megastore businesses Borders and Barnes & Noble dominated book sales in the United States (6). At its inception, many considered it inconceivable that Amazon would outcompete the big players, like Borders. The hesitation of this market giant, however, to adopt E-books or online shopping, which it instead outsourced to Amazon, contributed to its inability to keep up with the market and its collapse in 2011 (5).
Uber:
Similarly, the ride-sharing service Uber’s mobile model has allowed it to achieve higher capacity utilisation rates than traditional taxi services (7).
Uber adopted mobile internet technology for smartphones, with GPS, rating systems and the capacity for online payment, to allow efficient passenger-driver matching for a large network of drivers (8)(7). This has allowed Uber to provide their customers with a faster, cheaper and higher quality service with greater flexibility and transparency to better meet supply and demand than taxis (8)(7).
The more stringent regulations and outdated service provided by taxis has allowed them to be threatened by the rise and growth of Uber. The size of Uber’s operations will also make it increasingly difficult for taxis to regain their competitive edge, as the large number of drivers increases the likelihood of Uber being closer to potential customers (7).
Netflix:
Another example is Netflix, whose rapid digital adoption of the cloud enabled them to better serve customers and ultimately outcompete the market leaders, like Blockbuster. By migrating onto the cloud, Netflix could increase its capacity and provide flexible streaming services to customers worldwide on tablets, mobile devices and PCs (9), unlike the original competition.
The ability of these corporations to rapidly embrace and take advantage of digital advancements early on allowed them to not only dominate the market but dislodge much larger and established players.
Executives in successful businesses may underestimate the risk of digitally mature competition and fail to act fast enough to remain competitive (10). Technology creates rapid change in the competitive landscape, and the illusion of immunity resulting from success can lead to irresponsible complacency (10).
Even for incumbents, avoiding risk has become the greatest risk of all, where late adoption, not only lack of adoption, can be punishing if not fatal to businesses.
AI:
87% of survey respondents from a survey by Deloitte Consulting LLP in collaboration with MIT Sloan Management Review expected digital technologies to either moderately or greatly disrupt their industry (10). These new technologies threatening to disrupt industries today are AI, IoT and 5G.
Companies willing to rapidly adopt these advancements are most likely to become new market leaders, as shown in the cases above. However, companies who resist change, even established players, will increasingly fail to remain competitive.
But is your business ready to adopt or avoid AI?
Building a business case
The challenge many businesses face, however, is where to start their digital transformation. This can leave organisations wasting excessive time on deciding and researching which approach to take or leave them uncertain of success.
The proposed framework below allows businesses to use their processes and data to lead their transformation.
Identifying opportunities and a desired future state
Almost all challenges and opportunities faced by established enterprises today could be categorised into one of the following:
Customer engagement
Digital service delivery
Regulatory compliance and risk management
Process automation and transformation
Better operational decision making
Field services automation
Using the list above, businesses should identify the opportunities in their sector and for their organisation to create a vision of a desired future state.
The first step in building a business case is to map and prioritise these categories using your business objectives for the short to medium term.
Where to focus
Adopting AI has allowed businesses to boost their profit through a combination of cost reduction and revenue increase. Deciding where to focus AI initiatives within your business, however, could improve the expected financial outcomes of transformation.
The following table by McKinsey can serve as a sector specific guide to creating a focus and a starting point for your transformation, based on your business objectives (11).
As AI incorporates many different sub-components, when discussing AI, what comes to mind may vary from person to person. Most often, however, AI’s role in robotics and data science is at the forefront of what people consider to be AI’s most valuable contribution.
For businesses in your sector, though, the greatest value may be extracted from the implementation of AI in machine learning models, computer vision or natural language processing. To gauge the best features for initial AI investments for your business, we recommend evaluating the results of other companies’ investments within your sector across the spectrum of AI features.
Use the table below as a guide to decide which AI features to implement for the best business outcomes depending on your sector and areas of opportunity (11).
Clarify current state
In order to establish how to reach the desired future state, companies must first understand with clarity the current workings of their organisation; the details of how people work and what they do. This involves conducting a current state review or "AS-IS" analysis to understand the challenges and pain-points associated with your business priorities.
For businesses with difficulty gaining access to all relevant processes immediately, they should consider using data science to explore and discover the opportunities and gain insight into their current state based on data they already have.
Gap analysis
Companies should then perform a Gap analysis to understand current capabilities. A Gap analysis will allow businesses to establish how the corporation must be transformed to reach the desired future state, based on the current state, and provide an understanding of the cost, effort and benefits involved.
By understanding the costs and benefits associated with transformation, companies will be able to calculate ROIs with ease.
The above mentioned steps can be used to create a prioritisation matrix and identify the best opportunities for the organisation to pursue.
AI in digital transformation
Companies can implement AI through a process of digital transformation. As such, AI adoption should be considered as an ongoing initiative rather than a quick, one-time opportunity.
Nimbe are experts in enabling successful business transformations using AI and machine learning through our Affix-3 process. By gathering information from discussions and workshops with leadership and knowledge workers, we work alongside our clients’ organisations to help guide them through the process. In this way, our clients can discover their current state, goals and challenges, gain clarity of transformational opportunities through As-Is and Gap analyses and access support during implementation.
If you are planning to undertake a transformation or are actively engaged in a transformation journey, have a look at our readiness assessment tool here for a preliminary evaluation of your current state.
To find out how our discovery, clarity and implementation steps can help guide your company through a successful transformation, schedule a call with one of our consultants to discuss our AFFIX-3 Process.
References:
(1) http://sitn.hms.harvard.edu/flash/2017/history-artificial-intelligence/
(3) https://www.bbc.co.uk/news/business-48884596
(4) https://www.bbc.co.uk/news/business-44894420
(6) https://link.springer.com/chapter/10.1057%2F9781137409034_10
(7) https://www.nber.org/system/files/working_papers/w22083/w22083.pdf
(10) https://deloitte.wsj.com/cfo/2019/10/20/how-culture-drives-digital-transformation/