In today’s ever-evolving technological world, artificial intelligence (AI) has delivered powerful tools in terms of risk identification, user behaviour analysis, situational forecasting, and process monitoring. These technological innovations have provided early-adopters with unparalleled advantages relating to operational automation and promises continuing strategic benefits as the technology evolves. Anticipating these changes has allowed pioneering organizations to begin optimization efforts to:

• Allocate more resources to long-term strategic planning, and
• Free up personnel to work on tasks that require more creative thinking.

In the financial services industry, customers are already experiencing the benefits of cognitive technologies in their service packages. For example, Vanguard’s “Personal Advisor Services” (PAS) system automates many traditional tasks of investment advising such as portfolio monitoring. This frees up human advisors to take on higher-value organizational activities like sustaining excellent customer relationships through face-to-face interaction.
That’s not all – to date, a survey of Deloitte executives anticipates that organizations discussing AI for use hope to achieve the following outcomes:

51%: Enhance the features, functions, and performance of products
36%: Optimize internal business operations
36%: Free up workers to be more creative by automating tasks

No longer a futuristic concept, AI is quickly becoming a business requirement to achieve operational excellence. This may require a technological perception shift in order to accommodate how AI might integrate into our working world. Given AI’s powerful ability to disrupt job functions as they exist in present state, it’s understandable how AI critics create a dialogue often steeped in workforce scepticism, which can often translate to anxiety and unease on job futures. The first step is to dispel some common misconceptions:

1. The automation of repetitive tasks does not mean the automation of jobs. Instead, AI will create different opportunities as new needs arise.
2. Cognitive systems perform tasks that augment human activity. Currently, the tasks performed by AI are comparatively narrow within the context of the broader job function. For example, AI does work that cannot be done by humans in similar time frames, such as big-data analytics.
3. AI functionality is not meant to replicate or replace business relationships among stakeholders, particularly in cross-cultural relations.

At a fundamental level, AI supports business capabilities by automating business processes, and by offering insights through data analysis. RPA (robotic process automation) is the “least expensive and easiest to implement of the cognitive technologies…and typically brings a quick and high return on investment.” Meanwhile, cognitive insights from machine learning are increasingly detailed and data intensive, and thus offer more accurate and up-to-date predictions. The corresponding challenge? An organization’s ability to attract, acquire, and develop AI talent that sustains and grows the business. This “scarcity of cognitive technology talent” is the perfect opportunity to bridge the gap between emerging business requirements and new graduate millennials entering into an increasingly dynamic workforce.

Implementing AI may require a transitional change period to identify how AI can best serve business needs, but will ultimately allow organizations to arrive at solutions more efficiently. The time value savings derived from meaningful AI deployment allows for people, the true assets of an organization, to work towards other strategic objectives, such as fostering relationships with customers, or meeting with shareholders.


Davenport, Thomas H., and Rajeev Ronanki. 2018. “Artificial Intelligence for the Real World.” Harvard Business Review 96, no. 1: 108-116.

Ransbotham, Sam, David Kiron, Philipp Gerbert, and Martin Reeves. 2017. “Reshaping Business With Artificial Intelligence.” MIT Sloan Management Review, 59, no. 1: 1-17.

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