By Kirstie Tiernan, principal, BDO Digital
The portrayal of artificial intelligence (AI) in movies and science fiction often leaves workers fearing that they could be replaced by robots. While this fear is not entirely unfounded, it does require qualification.
The AI available today falls short in many of the ways that human thinking excels: AI is not good at emotion, metaphor, sentiment or morality. Machines require context, interpretation and oversight—all of which need to be provided by a live workforce.
One well-known example is Amazon’s resume rater, which gave each job candidate a star rating after it mined resumes submitted over a 10-year period. The machine learning technology was shut down once leadership discovered that the algorithm learned an implicit bias against women. Without intervention, machine learning technology will encode the biases that are pervasive in the human behavior it learns from.
While the original vision of AI was to mirror human decision-making AI cannot, and should not, render a human workforce redundant. In the near future, machines have the most potential to augment humans, create new job roles and help people work smarter.
The path to data analytics maturity starts with the availability, and cleanliness, of data. With a meticulously laid data foundation, your organization can operationalize analytics and, ultimately, tap the value of AI.
Man vs. Machine: How AI Will Change the Workforce
- Easily automated tasks will be tackled using intelligent automation.
Where there are manual tasks, and complex workflow steps, there is rich opportunity to inject automation to improve accuracy, save time, free up internal resources and dramatically improve business performance. One such task will be the collection, and organization, of data that will no longer be managed by humans.
- There will be less need for data scientists.
Previously, in order to bring data analytics and AI to a business, you needed to hire a data science team to gather, clean, and collate data and teach the system how to use it.
Today, as open-source engines become available, service businesses are emerging that make it easier for organizations to do data science without data scientists. As software becomes smarter, and more pliable, businesses will not have to reconfigure around the software. Rather, the software will adapt to fit the business.
- AI will inform decisions made in every role, in every department and create new roles.
As the automation transformation takes place, new roles will emerge including:
- Data Proctors: These employees will serve as subject matter experts who teach machines to enable higher-level learning and better application of knowledge.
- Data Deciders: When a condition arises that needs intervention, these employees will step in.
What Is Possible With Maturity?
When correctly leveraged, a mature data analytics program will save businesses time, reduce risk and boost financial return. Consider the following advantages of mature data analytics initiatives in action:
Create New Revenue Streams
A parking lot operator unlocked a new revenue stream by employing a computer vision model to track open parking spaces at a mall. The cameras identified the make and model of arriving vehicles—feeding that data to the mall for highly targeted advertising powered by machine learning.
Detect Fraud
A health care company used deep learning to review their accounts payable records and ensure there were no errors. Through this audit they spotted one vendor, and one year, that stood out as abnormal. The invoice line and invoice header did not add up, all to the tune of $13 million dollars.
Spot System Breakdowns
A manufacturer noticed a product was failing quality testing. To determine the issue on the manufacturing floor, they pulled data from their sensors and leveraged deep learning to spot anomalies. As it turned out, unlike everyone else, one worker was precisely following instructions that were out of date and needed to be updated.
Curb Costs
A logistics company was perplexed to see that cargo ships, taking the same route, sometimes used more fuel than others. By using deep learning, the company discovered that some ships lost radar connection for 12 minutes, at a particular point, and would temporarily drift off course. The company was able to predict when this would happen and recommend that ships go on manual at that point in the ocean.
Why Now?
Regardless of where your organization sits today, future-proofing your business depends on laying the groundwork for data analytics and AI maturity now. Your competition may not currently have the sophistication to anticipate the hazards that could derail profits or drive new revenue streams using customer data—but eventually they will.
In the proverbial data race, there will be winners and also-rans. By starting now, you can help ensure that your most valuable asset—your data—is used to edge out the competition.
To learn more about how data analytics can transform your organization, visit BDO’s Data Analytics Accelerator.
Kirstie Tiernan is a principal in BDO USA’s BDO Digital practice, in the Chicago office, with more than 16 years of experience providing data analytics, technology advisory and risk management services. Tiernan assists clients with generating key insights, and knowledge, from data across the organization in multiple sources, locations, systems, languages and functions. Contact info: [email protected] 312-616-4638
