As per a recent PwC survey, 90% of executives believe and see potential in the use of artificial intelligence (AI).
A report from PwC titled, “ 2020 AI Predictions: Five ways to go from reality check to real-world payoff,” reveals that organizations need to get the basics of the AI technology right before scaling up its use. Nearly all (90%) of executives surveyed mentioned that AI offers more opportunities than risks; however, in 2020, only 4% plan to deploy it enterprise-wide. In comparison, 20% of them said they intend to deploy AI in 2019.
Another report from PwC says that by 2030, AI is set to add $15.7 trillion to the global economy; however, its implementation is a major global challenge. In a bid to help organizations understand the power of AI to advance their business and to introduce it sustainably, the World Economic Forum (WEF) is working with experts and business leaders for AI toolkits that will help organizations. Streamlining of in-house processes is one of the top benefits company leaders expect from AI investments. The automation of routine tasks can help enterprises operate more efficiently and make substantial savings.
Nearly 40% of executives believe AI can be used to manage the threat of fraud and cybersecurity Since AI-based tools can recognize unauthorized network entry and identify malicious behavior in software. Organizations need to go beyond just offer training opportunities to scale AI. Employees should be able to apply the new skills they have learned to improve company performance. The report also mentions that having multilingual teams with both tech and non-tech skills integrated across the business is essential. This will help in collaborating on AI-related challenges and also decide which problems AI can solve.
Organizations need to have the processes, tools, and controls to maintain strong ethics and make AI easy to understand. They should also take measures to help employees see AI not as a threat to their jobs but as an opportunity to undertake higher-value work. A continuous increase in the usage of AI has also increased public fears about technology such as facial recognition. Several companies do not have centralized governance around AI, which could lead to an increase in cybersecurity threats. This also makes it harder to manage and secure technology.
A ‘test and learn’ approach is necessary to develop AI models. This is because algorithms are learning continually, and the data is being refined. Marketing and finance are some of the top use cases of AI as they work continuously as part of broader operational systems. Therefore, there has been an increase in the implementation of AI by IT leaders across multiple functions and business units. They are also integrating it with broader automation initiatives and data analytics.