Companies are approaching advanced technologies such as AI (artificial intelligence) with some skepticism. The first rule is to ask, what is the advantage? Can AI, for example, improve some aspect of the business? Sage, a cloud-related business management firm, examined the reaction of senior financial management in Canada to the digital transformation in progress today and issued a report on their findings.
The study found that while CFOs who embrace emerging technologies and data strategy are better positioned to drive change and growth across their organizations, 74% of respondents consider “modernizing business processes with technology” to be one of their biggest challenges. The report, CFO 3.0 Digital Transformation Beyond Financial Management, found that Canadian CFOs and senior financial professionals can no longer rely on making decisions based on historical data to respond to a VUCA (volatile, uncertain, complex, and ambiguous) business environment. More than two-thirds (67%) of respondents agree that cloud-based, data-driven financial management technologies are key to their future success.
Almost three quarters (74%) see data risks, including fraud and cyber threats, as one of the biggest challenges facing the profession, while 72% say fear of a security breach is the leading reason why they have not yet moved to the cloud. Even with cyber threats being a major concern, only 20% of respondents see ROI in investing in cybersecurity solutions.
Although 91% believe AI will be a benefit to the workplace in the long run, they also express high levels of concern and skepticism. For instance, 81% are concerned that AI will take over their jobs, 80% are worried about the ethics of AI, and 82% are concerned that they do not have the skills to operate AI-powered machines to their optimal capacity.
But others look at technologies like AI as unavoidable. A new McKinsey survey details the changes data and analytics have brought to industries. Many companies are still responding to technology shifts with ad hoc initiatives and one-off actions, rather than long-term strategic adjustments required for sustainable success.
McKinsey suggests companies embrace data-driven and collaborative models and invest heavily in capability building. Turning a diverse workforce into a cohesive, AI-educated group requires targeted learning. Meeting this challenge requires organizations to prepare their leaders, business staff, analytics teams, and end users to work and think in new ways. How? By helping them understand how to tap into AI effectively through data exploration, agile development, and interdisciplinary teamwork.
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