“Bridging the gap automation between BI and AI”: 4 insights from MIT Technology Review's report

The road is just beginning for companies embracing a transformation journey to become AI-driven. Such efforts are only undertaken in the hope of increasing innovation, speed and efficiency, not forgetting competitive and business advantages.

What are the findings of the studies conducted in 2022? What perspectives do they determine for 2025?

MIT Technology Review released a report based on a global survey conducted during the first half of 2022, of 600 CIOs, CTOs and other seasoned data executives who fully participate in Artificial Intelligence and Machine Learning initiatives.?

“Information is the oil of the 21st century, and analytics is the combustion engine.” — Peter Sondergaard

1) Data: the New Oil of the Digital Transformation Journey

Data infrastructure in many enterprises is too often perceived as a necessary evil. Although you overheard the “New Oil” analogy, at the AI stage of the Digital Transformation journey, data is more than ever critical. Even though having the most efficient algorithms, applications, servers or AI experts is crucial, the fact remains that you cannot achieve any of your AI goals without the right datasets.?

Inadequate data management or infrastructure is a real obstacle when it comes to putting Artificial Intelligence to action. The report reveals that 72% of the technology executives surveyed agree that “data issues are more likely than not to be the reason”.

A paradigm shift is needed for enterprises to see their overall data infrastructure as a profit center instead of a cost center.

For many companies, their data infrastructure is still a cost center today. They must now consider their data as a business asset. This is very well understood by the executives surveyed. 78% claim to invest in data areas including, security, governance or new data and AI platforms.

“Data is the new science. Big Data holds the answers.” — Pat Gelsinger

To complete this quote, it is appropriate today to add: “... and Artificial Intelligence unleashes its power”.

2) AI application in core functions of the business

According to the survey, “less than 1% of the respondent companies can be considered AI-driven today”. Encouragingly, it also shows that "the percentage not using AI will drop by nearly half across all business functions".?

This naturally leads to a trend towards a certain democratization of AI within the enterprise in the sense that we expect a broadening of the spectrum of use cases.

Looking ahead to 2022 (cf figure #1 of the report), it is interesting to note that large-scale adoption of AI use cases is primarily concentrated in finance and IT. Now, if we study the projections in the very short term (2025) we can see that the use cases will indeed extend to other areas of the company such as marketing, sales, product development and supply chain for example. The widespread use of AI is gradually becoming a standard tool in the digital transformation arsenal.

3) AI concrete use cases

Some companies are still struggling with BI projects, having trouble finalizing their data warehouse or getting lost in implementing an effective data lake initiative. At the same time, AI-aware companies are already offering value-added services to their customers, including personalized recommendations and advice based on AI technologies and methods.??

We are witnessing an evolution of concrete use cases of AI within the company by 2025. Here are some examples illustrating the diversity and relevance in the company's strategy, in direct contact with the business:

• Enhanced chatbots for employee and customer interaction,
• More precise prediction of inventory needs using analysis of omnichannel transaction data,
• Climate change: Optimizing energy and water consumption in manufacturing,
• Refining underwriting through monitoring and analysis of driver behavior,
• Predicting failure of engine parts to streamline service and reduce warranty costs,
• Expanded product personalization for omnichannel experiences,
• Next-gen retailing platform, including offers and dynamic pricing…

4) Data and Humans best asset of AI-driven company

To date, the leaders who responded to the survey have clearly identified Data as the primary source of effort in developing a true AI platform that can address their business challenges. In fact, 72% of them say that data-related issues are the biggest risk compared to other factors, when they see what is likely to jeopardize the achievement of their AI goals by 2025.

The survey shows that 32% of these leaders identify topics such as the democratization of data (internal and/or external data sharing), 24% the need to improve data quality, and more generally 32% the issue of Business Intelligence/analytics infrastructure and tools.

To take the BI tools example, only 27% of the Global CIO prioritize it by 2025. Indeed, focusing on AI tools will increase the need to develop the human talents acquisition and retention the development of their skills, at 41%.

Echoing this, Vittorio Cretella, Chief Information Officer at P&G for example, says “Enabling the ‘democratization’ of AI involves building a set of algorithmic platforms that have intuitive front ends”. He relegates AI to its proper place. It is a tool. By saying this, he asserts that people produce value by using these tools/platforms. Hence the urgency to make these tools accessible to the greatest number.

CONCLUSION

In this article, I wanted to highlight four points that I think are important to note. Do not hesitate to read the full MIT Review article (reference below) and share back the points that are most important to you.

1. Even if it sounds like an old saying, Data is a real treasure for companies. They must exploit it in its strategy to become AI-Driven,
2. Today, the number of companies that consider themselves AI-Driven does not exceed 1%. This illustrates how far the business world still has to go in this area,
3. Recently, the use cases of AI in enterprises (apart from the industry field) have gone beyond the classic IT or Finance use cases,
4. Finally, it appears that, just as Digital Transformation, AI is not only a matter of technology. The path that will lead companies to make the most of Artificial Intelligence technologies must put people at the heart of its strategy.

CIOs are fully aware that technology is evolving and that the platforms they build today to sustain their AI initiatives will need to match that evolution. The way they understand and manage their data should also drive this progressive evolution.

In their efforts to modernize and adapt their technical infrastructure, CIOs must be committed to the Big Data wave's credo by making secure, governed enterprise data accessible to all. This way they will be able to build an actionable AI platform.

“Competing in the age of AI is not about being technology-driven per se …/… Those uniquely human skills of creativity, care, intuition, adaptability, and innovation are increasingly imperative to success” - Nada R. Sanders and John D. Wood

In addition to this study, we can look ahead in perfect agreement on the postulate that the enterprise AI-Driven vision’s main focus is the people. Nada R. Sanders and John D. Wood lay out a four-level framework showing organizational leaders how they can "create a human-centered organization with superhuman intelligence". But that's another story...

Sources/References: MIT Reviews Insight: "CIO vision 2025 - Bridging the gap between BI and AI", HBR: The Secret to AI Is People