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AI in the Accounting Big Four – Comparing Deloitte, PwC, KPMG, and EY

As with most large consulting firms, Deloitte vies for market share and press through thought leadership – and like the other Big Four – it has increasingly focused it’s white papers and research on the topic of artificial intelligence.

The company claims that this technology has helped reduce the time spent on reviewing legal contract documents, invoices, financial statements and board meeting minutes by up to 50 percent or more.

Following are some business use-cases as a result of this partnership: Deloitte Catalyst – another recent AI initiative from the global consulting giant – is a network of startups, that are working together to translate AI technologies into practical business solutions for client firms.

Most AI firms are still figuring out exactly how to drive business value with their technology, and Deloitte hopes to forge partnerships with these cutting-edge firms to help bring the latest AI innovations to their clients.

“Technology like AI can help make these processes more efficient, accurate and comprehensive, helping us get better insights to clients sooner, and empowering our professionals to deliver high-value services to our clients”.

They claim that this reduces the administrative time spent on reviewing audit documents and gives employees more time to participate in the judgment and analytical part of the process.

According to EY Global Assurance Innovation Leader Jeanne Boillet in a June 2017 report: “These pilots show that AI tools would make it possible to review about 70%-80% of a simple lease’s contents electronically, leaving the remainder to be considered by a human.

With more complex leases (in real estate, for instance), that figure would be more like 40%, but as the tools improve, and the machines learn, it is likely that more complex contracts and data can be read, managed and analyzed.” Another area where EY has applied AI technology is the automation of routine tasks, such as auditing (which we covered in greater depth in our full article on AI in insurance), by using it’s own proprietary Robotic Process Automation (RPA) system.

For example, this drone can count the number of vehicles in a production plant under audit, and communicate this data directly into the EY Canvas – the global audit digital platform.

We find the word “never” to be downright ridiculous, but we cannot blame EY leadership from having to tout this opinion, and there is no reason to blame Mrs. Boillet for being so black-and-white about the matter, anyone in her shoes would say the same thing.

Many would argue that businesses of this kind (chock full of knowledge workers working in spreadsheets) are among the biggest “low-hanging fruit” for automation, and it behooves older people-heavy businesses to dispel disturbing thoughts about massive layoffs.

The impact on employee morale and shareholder value would likely be tragic if EY’s leadership (or the leadership of Accenture, Deloitte, or any other large consulting firm) were to state openly that many of their current jobs may be fully automated, and that some of these jobs would not be replaced.

We should expect to see large, people-heavy legacy companies (For more insight into the kinds of jobs that might be first – or last – to automate, read or listen to our previous interviews with Martin Ford, Kevin LaGrandeur, and Marshall Brain – all of which are focused on the impact of automation on the job market.) The second largest professional services firm by revenue, PwC, claims to have begun adopting AI as well.

we have helped large auto manufacturers visualize and navigate over 200,000 go-to-market scenarios to fine-tune their strategy and launch a new multi-billion dollar business in ridesharing and autonomous/electric vehicles.

A recent PwC analysis of the financial services sector identifies a number of automation and augmentation concerns related to AI – and advice from PwC on how firms might adapt to AI in the future.

The image below is only a small snapshot, because of the complexity of the topic (and the inherent challenges in predicting the future), we advise the reader to assess multiple sources and develop their own conclusions.

Key features of KPMG Ignite include AI tools (a few examples of which are listed below), AI integrators to make these tools compatible with existing IT infrastructure, guidance for client firms and testing, prototype development, and innovation on emerging AI applications.

Like Deloitte, they’ve created a number of layperson-friendly AI explainer videos to explain AI’s potential impact on their work: KPMG’s “ethical compass for automation” highlights some of the societal concerns that they consider to be important in the years ahead.

In the world of startups, companies increasingly see their competitors use “artificial intelligence” in pitch decks and on their “about” page – and the pressure mounts to do the same (even if they have no AI skills or talent, and even if the product is in no way predicated on artificial intelligence).

For some reason I find that business readers often know intuitively that a startup’s pitch deck is self-serving, but they’re often unable to apply that same “taking it with a grain of salt” mentality to white papers and reports, which – like pitch decks – serve the goal of filling a company’s bank accounts, not of portraying truth for its own sake.

These companies have massive revenues and thousands of talented people – and based on our assessment, all four of the Big Four claim to have integrated AI into some of their service offerings, and we’d suspect that this is, in fact, the case.

Indeed part of our job here at TechEmergence is to do the “digging” ourselves and aim to get behind the bluster of press releases, but we’d like to remind our readers to think like an analyst as they consume information that might affect their strategy and procurement.

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