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The top choices for 2021 AI and analytics priorities all—inevitably—have one thing in common: They cross the entire organization. That’s because AI does too. Unless your company is already effectively sharing data, subject matter expertise, governance and AI models across teams and functions, you are going to have to reorganize so that you can collaborate as needed.
AI reorganization goes beyond breaking down silos. It also requires a cultural shift so that everyone’s decisions become more based on data—and the simulations and forecasts that AI produces from that data. It also requires integrating machines that think and learn—and teach themselves to learn even better—into your organization. When AI models are constantly improving themselves, your decisions can constantly improve too. Your company will need to be ready to pivot quickly, not on a yearly planning cycle, but few organizational flow charts are currently set up for that kind of speed.
This organizational transformation may sound like a tall order, but it needs to happen. Our survey results show this is the case, because the easiest AI and analytics application—automating routine tasks—is no longer a top priority for many businesses. This year only 25% cited it as a top priority going forward. In last year’s survey, 35% did. This drop is certainly not because automating routine tasks isn’t a highly profitable use of AI. It is. But many companies have already advanced well beyond that point, and their current priorities are more strategic uses of AI, for which reorganization is inevitable.
How to reorganize for AI
Bring the three A’s together.
When AI, analytics and automation are part of a unified effort—either through a centralized hub or centralized governance—you increase your ability to monetize data, build a data-driven culture and reduce risk along the way.
- Pick the platform.
Give AI the technical foundation it needs, including a platform architecture suited to your unique data sources, business processes and use cases. Some businesses will want to build this platform in-house. Others will find it more cost-effective to rely on third-party providers.
Recenter on new opportunities.
To identify and seize the new business opportunities that AI’s simulations and forecasts offer, you’ll need continuous collaboration between engineers, data scientists and the line-of-business managers and staff. To avoid friction, establish clear handoffs and lines of communication.
Learn about the five predictions and what your company can do to make the most of AI
About the survey
PwC’s annual AI Predictions survey, now in its fourth edition, explores the activities and attitudes of US business and technology executives who are involved in their organization’s AI strategies. Among this year’s 1,032 survey respondents, 71% hold C-suite titles and 25% were from companies with revenues of $5 billion and up. They are from the following industries: industrial products (20%), consumer markets (20%), financial services (18%), tech, media and telecommunications (17%), health industries (17%), and energy, utilities and mining (8%). The survey was conducted by PwC Research, PwC’s global Center of Excellence for market research and insight, in October 2020.
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