6 key areas that will separate the AI leaders from laggards
What’s on the horizon for artificial intelligence in 2019? There are certainly of theories floating about, but consulting firm PwC predicts that organizations that focus on six key areas will become AI leaders.
Here are the areas companies need to focus on in 2019 to be ahead of the competition when it comes to AI, according to the firm:
Organize for return on investment (ROI) and momentum
Pressure will increase to scale up AI in 2019 to enhance decision-making and provide forward-looking intelligence for users in every department and function. Having the right AI governance model enables companies to develop use cases that create quick wins.
Teach AI citizens and specialists to work together
AI is being democratized, but is still so complex that even trained business specialists can make mistakes. Organizations need to develop the right mix of citizen users, citizen developers, and data scientists, and give them the tools, training, and incentives to help them work collaboratively.
Make AI responsible in all its dimensions
Customers, employees, boards, regulators, and corporate partners are wondering if they can trust AI. To answer that affirmatively, organizations need to assign accountability for fairness, interpretability, robustness, and security, governance, and system ethics.
Locate and label to teach the machines
AI can help organizations manage risk, make better decisions, improve document classification, and automate customer
operations. But first they must label, standardize, and integrate data to train AI.
Monetize AI through personalization and higher quality
Increasing the top and bottom lines with AI is not a distant dream. AI’s power can help companies create and market high-quality, personalized, data-driven products and services. Companies can use AI to help with strategy, invent new business models, and transform their organizations.
Combine AI with analytics, the Internet of Things (IoT), and more
AI’s power grows when it is integrated with other technologies, such as analytics, IoT, blockchain, and eventually, quantum computing.