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AI and Analytics

It’s not an exaggeration, but a demonstrable fact: artificial intelligence (AI) and analytics are transforming how business does business. From back office automation to front office transformation, from changed skills, cultures and ways of working to new go-to-market strategies and business models, AI is everywhere.

When a set of technology tools can do so much — and requires so much organizational change — it can be hard to know what goals to set and what paths to take or accelerate. Many companies today are still prioritizing AI’s “traditional” role: to make operations more efficient and productive. The majority report that these efforts are paying off. But in a sign of AI’s maturity, over two-thirds report benefits today from AI initiatives to improve the customer experience. Roughly half are seeing payoffs from AI to drive innovation, revenue growth, cost savings, better decision-making, employee training and risk management.

Bar chart titled
Where companies expect AI payoff — and whether they are getting it
Ranked as top-three priority
Currently realizing AI benefits
Operate more efficiently/increase productivity
%
%
Innovate our products and services
%
%
Grow revenue
%
%
Create better customer experiences
%
%
Achieve cost savings
%
%
Improve internal decision-making
%
%
Enhance employee training and upskilling, including remotely
%
%
Reduce risks
%
%
Improve talent retention and recruitment
%
%
Q: What are the primary goals of your company’s AI strategy? To what degree have your AI investments in the following areas lived up to expectations — Currently realizing benefits from AI. Source: PwC AI Predictions 2021. Base: 1,032

Yet for many executives who aren’t AI specialists, key questions remain: How does AI work, exactly — and what kind of work can it do? How can you make your AI more trustworthy, so that it helps you make decisions that are both accurate and fair? What AI priorities are companies across the US setting? Read on to find out the answers.

Get up to speed on AI and the most pressing business issues

Artificial intelligence explained

Learn about nine types of AI and what they can do for your company.

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Understanding algorithmic bias

Why it happens and how to build trust in AI.

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AI predictions 2021

How to navigate the top AI trends facing your business.

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What it means for business execs 

As AI becomes integrated in more business processes, it’s even more important to get it right — and it’s every executive’s responsibility. Challenges include allocating resources and making acquisitions wisely, taking measures to scale up AI (and achieve greater return on investment), controlling risks and building an AI-ready organization. With those challenges addressed, your odds rise of becoming — and remaining — an AI leader.

 

See what analytics and AI means for your industry or area of the business:

To operationalize AI, reorganize in these three ways

What it takes to scale AI across your business.

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AI and M&A: Are you getting the value you paid for?

Extracting value when acquiring AI companies.

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Sector insights: AI predictions 2021

Top industry findings from our annual survey.

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How companies are realizing value 

AI isn’t easy, but PwC’s globally recognized AI capabilities — most recently ranked as a leader in The Forrester Wave™: AI Consultancies, Q1 2021 rankings — are helping many companies get it right. Our experienced team and ready-to-go digital accelerators are helping companies with key analytics and AI challenges: developing and assessing strategy, enhancing and monetizing data sets, upskilling talent, building an AI-ready operational model and culture, upgrading technology, creating and maintaining AI models, optimizing potential acquisition strategies and establishing governance and managing risks.

Learn how others are capitalizing on analytics and AI in a responsible and trusted way:

Insurtech case study

Insurance claims estimator uses AI for efficiency

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LiveRamp case study

Core business changes: Unlocking value for LiveRamp through a complex carve-out

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Microsoft case study

Prioritizing ethics and integrity: How Microsoft uses data analytics to fight corruption

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How can we help you do the same:

Analytics and AI Transformation

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