As artificial intelligence (AI) assumes more of the internal workload and serves up more predictive and prescient insights, organizations are recognizing its value. The rise of AI has in turn put a spotlight on today’s data architecture – the fuel that ignites the intelligence.
With customers gravitating to online sites, mobile apps and smart devices that are more convenient, informative and engaging, data is central for businesses seeking to deliver a differentiated experience. Data and intelligence can not only enhance the customer experience, they can improve process efficiency, automate tedious tasks, and quickly uncover previously hidden insights. AI-ready data architectures have helped transform organizations and industries.
However, many companies are straining under the weight of an unprepared data foundation that has thus far limited the technology’s achievements. Between 60% and 73% of all data in an enterprise goes unused for analytics, according to Forrester Research.
In these early days of AI adoption, many organizations are finding the true potential – and ROI – to be elusive. Many projects and programs are failing to meet high expectations, delivering incremental benefits rather than exponential improvements.
Laying the foundation with a modern data architecture
We advise organizations to more fully embrace AI, which includes making data-driven decisions internally and throughout their ecosystem. Specifically, they should adopt a modern data architecture as the first step toward becoming more adaptive to the continuously changing customer and economy. This means having a scalable data and analytics foundation, so businesses can treat data as an asset and support AI deep learning to deliver insights, operate with precision, and achieve the outcomes that drive competitiveness.
Here are some ways AI and the critical role of a modern data foundation help create a more adaptive, prescient organization:
Figure 1
1 Uncover previously hidden influences on machines and humans.
AI can solve complex business problems by exposing trends from data patterns. Moreover, because it’s free of the (often unconscious) bias that affects humans, AI can uncover hidden influences. For example, resource-heavy and labor-based companies use AI to understand the apparent randomness of workplace injuries. By analyzing incident reports and worker data, we established a system that helped an organization identify the likelihood that a worker would get hurt on the job, what injury might occur, and at what time.
2 Understand what technology and resource investments are necessary.
AI is being put to use throughout back-office, customer service and compliance operations to eliminate repetitive administrative tasks and support services more cost-effectively. This is especially true within banking; a Wells Fargo & Co. analyst estimated that large financial institutions are spending a combined $150 billion annually on AI systems.
3 Create new processes and business models.
Many organizations’ adoption of AI may be through intelligent process automation (IPA), which deploys smart bots to address and improve rote tasks. A more valuable application, however, is the use of IPA to help determine the best process to follow or business model to use. For example, one UK municipality is using smart bots to quickly inform homeowners whether they need to seek planning permission for a property expansion or remodel. Following a guided process aided by bots, the homeowners can share their plan and determine if it’s in compliance with housing standards according to the latest rules and guidelines.
4 Foster an environment in which employees can transition skills and adapt to new roles.
AI is redefining the future of work, from skilling incoming workers to retraining existing workforces. According to a 2019 RELX survey of 1,028 U.S. senior executives, 62% of business are offering AI training, up from 46% in 2018. The study notes that more organizations are using AI technologies than are offering AI training, which might indicate a lack of efficiency and missed opportunities for maximizing organizational potential. To address the gap, organizations looking to increase their AI bench strength can reskill and mentor associates who presently leverage data, such as business analysts, to gain rudimentary AI skills. Organizations also should seek to partner with universities to attract new talent.
5 Provide customers a more rewarding and engaging experience.
Today, most organizations use data primarily to better understand customer behavior and expectations, according to a study by Exasolt. AI further enhances decision-making to improve the customer experience by reducing interaction time and process friction (Netflix and Uber are notable adopters).
Today’s adaptive enterprise should look for new ways to instate AI with other emerging technologies, such as edge computing, blockchain and virtual reality. Now is the time to experiment with new technologies incubating in labs where the inventors are open to exploring commercial applications.
To learn more about AI and its growing role in today’s environment, join us Thursday, Jan. 30, 2020, as Bret Greenstein, SVP and Global Head of AI at Cognizant, and Michele Goetz of Forrester Research discuss how AI prepares companies to win in the new economy. Click here to reserve your place.
