AI and Data Strategy: Where Do They Intersect?

Image credit: /
  • “Nitish Mittal, a partner in the digital transformation practice at Everest Group, emphasizes this point: ‘I can’t stress this enough: data or the lack of the right data strategy is the number one bottleneck to scaling or doing anything with AI. When clients come to us with what they think is an AI problem, it is almost always a data problem. AI depends on viable data to prosper. That’s why it’s important to think about the data first.’
  • Beena Ammanath, executive director of Deloitte AI Institute, stresses quality over quantity: ‘It’s not enough to say you have 20 years of data. You have to have the right data. You may have high quantities of data, but you may not have the quality you need. Many companies don’t have a data architecture capable of pulling in data from different places and cleaning it up so it’s usable for AI technology.’”

Catching Up Fast by Driving Value From AI

“Back in 2019, Porter and Thomas decided that the primary focus of the bank’s analytics and AI activity should be customers — hence the “customer insights, data, and analytics” label. Thomas, Lee, and their colleagues felt that improving processes and making better decisions within the bank was the best way to catch up to and surpass competitors.

Thomas felt that, given the bank’s relatively late start, a results-oriented approach to AI was necessary. That’s why there are no “big bang” projects, and there is little pure experimentation or research. Instead, the bank’s key use cases focus on continuous improvement of its operations and customer relationships. Lee told us that as a result, most AI projects are deployed into production, with about 80% of Scotiabank’s analytics and AI models already in place and the other 20% pending.”

The Data Paradox: Artificial Intelligence Needs Data; Data Needs AI


“‘A new generation of enterprise analytics is emerging, and it incorporates some degree of both automation and contextual information,’ according to Tom Davenport and Joey Fitts, writing in Harvard Business Review. AI-enhanced analytics systems ‘can prepare insights and recommendations that can be delivered directly to decision makers without requiring an analyst to prepare them in advance.’”

Why Digital Transformation Always Needs To Start With Customers First

  • “AI and machine learning are considered essential to digitally transforming organizations and making all processes more customer-centric, with 41% of CEOs saying these technologies will improve data governance and data analytics capabilities.
  • Enterprises that have customer centricity and a data-driven mindset are the most likely to succeed with a digital transformation initiative.
  • 62% of organizations say delivering an excellent customer experience as measured by customer satisfaction scores defines success as a digital-first business, according to a recent IDG study.”

How Small Businesses Can Leverage AI to Battle Bigger Competitors

  • “In fact, 54 percent of executives have said that AI has already increased their business productivity. Charlie Burgoyne, founder and CEO of Valkyrie, an Austin-based AI-consulting firm, believes that the technology is particularly critical for up-and-coming startups to help reduce burdensome operations.
  • A recent MIT Technology Review Insights survey of more than 1,000 business leaders discovered that 87 percent of respondents have begun deploying AI in their business, with most implementing various programs to improve customer service.
  • 96% of marketers agree that efforts to personalize a business transaction or experience will help to advance the customer relationship.”