Five Critical Capabilities Business Leaders Need to Generate Value from AI Applications
You already know that AI apps can manage everything from scheduling manufacturing equipment for timely maintenance to processing loan applications to detecting identity fraud.
Most executives agree about the potential of AI to transform their businesses. But among those that have adopted AI tools, many can’t pin down measurable successes.
Research undertaken by MIT Sloan revealed that many organizations hadn’t benefited from AI tools because they hadn’t developed the organizational capabilities and practices required to integrate AI applications into their business processes.
In AI in Leadership from MIT SA+P and MIT Sloan, you can explore how you can prepare your organization for innovations surrounding AI.
Five critical capabilities to create value from AI applications
According to the research from MIT Sloan, for AI tools or enterprise cognitive computing (ECC) to create value in terms of cost reduction, generating revenues or improving business processes, businesses need five key capabilities:
Data science competence
AI or ECC tools depend on vast amounts of data, which entails collecting, cleaning, curating, tagging and analyzing internal and external data from multiple sources. It also means defining the relationship between the data and the AI algorithms. Hence, data scientists with expert knowledge of natural language processing, statistical inference, knowledge representation and learning algorithms will be an important resource for a company trying to create value from ECC.
Business domain proficiency
When it comes to AI tools, business domain proficiency is the art of linking data science competence to business value. It’s not enough to have technical expertise. Business leaders need deep process knowledge. In addition to understanding tasks, workflows and logic of existing business processes, they need to envision how ECC apps can improve them. An AI app can easily categorize or predict something with the input of vast amounts of data. But just that won't improve the business.
Enterprise architecture expertise
The more robust the AI application, the more business processes it will affect. This can require enterprise architects to redesign systems, processes and roles across different business verticals. Enterprise architects can perceive how jobs will evolve and concurrently, the need to up-skill, re-skill and possibly create new roles. The role of the enterprise architect is especially crucial given its breadth and often falls on the business leader with experience in technology-driven transformations, change management and organization design.
Operational IT backbone
Successfully integrating ECC applications means relying heavily on a company’s current technologies and data foundation as well as the people responsible for the development and running of these apps. A business’ IT foundations need to support the storing and accessing of critical data, integrating AI tools with other apps, providing reliable operations and ensuring privacy and security. No enterprise application operates in isolation and if ECC apps aren’t integrated properly, they’ll be challenging to use and will be ignored.
AI applications work by predicting an event based on possibilities, not by providing a definitive answer. End-users need to apply human judgment to make conclusive decisions. This requires digital inquisitiveness –- the tendency to question and evaluate the data before them and improve outcomes. Executives have to learn how to use data in effective decision-making, deal with poor data, build decision trees, teach an algorithm to detect patterns and develop models to solve problems.
These five capabilities will prepare an organization to derive the most value from ECC applications. To deliver on the above capabilities, a company must apply them.