Artificial intelligence (AI) offers a major opportunity for global businesses, as the technology could add up to $15.7 trillion to the global economy by 2030. However, many businesses still struggle to actually use AI throughout the business to drive value and ROI, according to a Wednesday report from PwC.
Of the 1,000 US executives surveyed, 20% said their companies will deploy AI across their businesses in 2019. However, major concerns over new privacy threats (43%), new cyberthreats (41%), new legal liabilities and reputational risk (34%), the technology's complexity (33%), and an inability to meet demand for AI skills (31%) stand in the way of implementation.
Companies must focus on the following six key areas to become AI leaders, according to the report.
SEE: IT leader's guide to the future of artificial intelligence (Tech Pro Research)
1. Structure: Organize for ROI and momentum
Businesses will feel pressure in 2019 to scale AI initiatives to improve decision-making and forward-looking intelligence for workers across every department and function, PwC predicted. The right AI governance model allows organizations to develop use cases that create quick wins, while also providing reusable tools for other AI projects to build upon.
2. Workforce: Teach AI citizens and specialists to work together
While AI is being democratized, it's still complex enough that business specialists still make mistakes. Businesses should develop a mix of citizen users, citizen developers, and data scientists, and giving them tools, training, and incentives to work together.
3. Trust: Make AI responsible in all its dimensions
Businesses must assign accountability for AI bias, interpretability, robustness, security, governance, and system ethics, to ensure that AI can be trusted, the report said.
4. Data: Locate and label to teach the machines
AI has the potential to help companies manage risk, make better decisions, improve document classification, automate customer operations, and more, the report noted. But first, businesses must prioritize labeling, standardizing, and integrating data to train AI, to allow AI to find patterns, and provide insights into the future.
5. Reinvention: Monetize AI through personalization and higher quality
AI can help businesses create and market high-quality, personalized, data-driven products and services, and companies can use the technology to help with strategy, new business model creation, and ultimately, business transformation.
6. Convergence: Combine AI with analytics, the Internet of Things (IoT), and more
Integrating AI with other technologies including analytics, IoT, blockchain, and quantum computing will grow its power, the report noted. Businesses can use DevOps to manage this convergence by bringing employees together to keep projects moving smoothly.
- Executive's guide to AI in business (free ebook)
- Google's image recognition AI fooled by new tricks (ZDNet)
- How to become a machine learning engineer: A cheat sheet (TechRepublic)
- IBM Watson: What are companies using it for? (ZDNet)
- How to prepare your business to benefit from AI (TechRepublic)
Alison DeNisco Rayome has nothing to disclose. She does not hold investments in the technology companies she covers.
Alison DeNisco Rayome is a Senior Editor for TechRepublic. She covers CXO, cybersecurity, and the convergence of tech and the workplace.