Applications of artificial intelligence in business: More than meets the AI

Joseph A. Gill

Joseph A. Gill

Artificial intelligence (AI) is not a novel concept within history or pop culture (think Egyptian automatons1, C-3P0 or SKYNET). However, the adoption of AI in mainstream society has seen exponential growth in the last five years. In the second annual Technology Trends Outlook published by the McKinsey Technology Council2, applied AI once again earned the highest score for innovation in the report. This article is for business owners and employees who want a quick commentary on how the use of AI can transform the business sector.

What is AI?

“Artificial Intelligence” can be defined as a set of computer techniques that enable a machine (e.g., a computer or mobile telephone) to perform tasks that typically require intelligence or engages in humanlike activities, such as reasoning, planning, or learning.

Three Types of AI

Companies should consider AI through the lens of business capabilities rather than technologies. Supported by a Harvard Business Review (HBR) study of 152 projects, AI can support three important business needs: automating business processes, gaining insight through data analysis, and engaging with customers and employees.3

Process automation

Annie Quangtakoune

In the HBR study, the most common type of AI technology being implemented was the automation of digital and physical tasks using robotic process automation (RPA) technologies (46.7 per cent). Tasks include:
• transferring data from e-mail and call center systems into systems of record;
• reconciling failures to charge for services across billing systems by extracting information from multiple document types; and
• “reading” legal and contractual documents to extract provisions using natural language processing.4

Cognitive insight

The second most common type of AI technology being used in projects uses algorithms to detect patterns in vast volumes of data and interpret their meaning (37.5 per cent). These machine learning applications are being used to:
• identify credit fraud in real-time and detect insurance claims fraud;
• automate personalized targeting of digital ads; and
• provide insurers with more-accurate and detailed actuarial modelling.5

Cognitive engagement

The least common type of AI technology within the HBR study engaged employees and customers using natural language processing chatbots, intelligent agents, and machine learning (15.8 per cent). This category included:
• intelligent agents that offer 24/7 customer service;
• internal sites for answering employee questions on topics including IT, employee benefits, and HR policy; and
• health treatment recommendation systems that help providers create customized care plans for patients.6

To get the most out of AI, companies should:
1. Learn what AI can and cannot do ~ This empowers companies to make more informed decisions about whether adding a new technology or application will improve their workflow and meet the needs of their organization.
2. Think about their end goals ~ By creating a prioritized portfolio of projects based on business needs, companies can capitalize on the end-first process to refine the list and measure success.
3. Develop plans to scale up across the company ~ This will include evaluating internal capabilities to adopt the technology, building or integrating a system, testing the system, and making refinements.

Canada’s AI regulation landscape

On June 16, 2022, Bill C-27, formally called the Digital Charter Implementation Act, 2022, was introduced in Parliament for its first reading. This Bill includes the Consumer Privacy Protection Act (CPPA) (a revamped version of Canada’s current federal privacy legislation) and the Artificial Intelligence and Data Act (AIDA).

The CPPA is aimed at updating the Personal Information Protection and Electronic Documents Act (PIPEDA), which sets the data protection rules for federally-regulated industries and for provinces that do not have their own private-sector privacy laws.

It would create a new tribunal to hear requests from the privacy commissioner to levy heavy fines for firms that violate the CPPA. The AIDA is new legislation forcing businesses deploying “high impact” AI technologies to use them responsibly. The AIDA does not currently define what constitutes a “high impact” system but states that the federal government will establish its formal definition through regulation later. An AI data commissioner would enforce regulations.

Bill C-27, if adopted into law, would represent a significant change to the legal framework governing Canada’s AI sector and impact businesses by creating new governance and transparency requirements for those who make, use, or work with AI. The Bill would also introduce significant penalties for non-compliance with several new obligations in the AI sector. As currently drafted, the federal government has created flexibility in how the Bill will be implemented and enforced, and the scope of application of the AIDA intentionally leaves room for the enactment of provincial AI laws. Still, many of the specific details related to obligations and requirements for
the AI sector will not be fleshed out until Parliament debates the Bill.7

In the interim, those looking to implement best practices in preparation for Bill C-27 can look to existing soft law frameworks on AI, such as the Responsible AI Impact Assessment Tool developed by the International Technology Law Association.8

In Conclusion

As government looks to introduce legislation to regulate AI, companies should keep an open mind to the potential applications of cognitive technologies and how they will impact their sector. The HBR study suggests that there is more success when the application of AI is on an incremental rather than transformative basis and when focus is on augmenting rather than replacing human capabilities.9

Further, companies would benefit from considering how these technological initiatives will affect their partners or resources in their markets. As with any innovation, we can expect to see a continuation of new startups, increased applications in business and consumer use, some workforce displacement, and likely a shift to specialized skills. Companies with stronger networks of relationships will be better positioned in a world transformed by these technologies.10

A business that is considering a technology project should consult legal counsel. McKercher LLP has groups of lawyers who have considerable experience assisting businesses with technology projects, regulatory compliance, as well as the implementation of new technology such as AI and blockchain.

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1Gaston Maspero (2009). Manual of Egyptian Archaeology: A Guide to the Studies of Antiquities in Egypt. BoD. p. 108. ISBN 9783861950967 and Al-Masry Al-Youm. “Ancient Egyptians invented first robot 4,000 years ago: study”. Egypt Independent. Sept 21, 2022. https://egyptindependent.com/ancient-egyptians-invented-first-robot-4000-years-ago-study/
2Michael Chui, Roger Roberts, Lareina Yee. “McKinsey Technology Trends Outlook 2022”. McKinsey Technology Council. Aug 24, 2022. https://www.mckinsey.com/capabilities/mckinsey-digital/our-insights/the-top-trends-in-tech; The McKinsey Technology Council is a global group of over 100 scientists, entrepreneurs, researchers, and business leaders.
3,4,5,6Thomas H. Davenport and Rajeev Ronanki. “Artificial Intelligence for the Real World”. Harvard Business Review, January -February 2018 issue (pp. 108-116). https://hbr.org/2018/01/artificial-intelligence-for-the-real-world.
7So far, the House of Commons committee on ethics, privacy and access to information has not set dates for hearings.
8International Technology Law Association. Responsible AI: A Global Policy Framework.
9Supra Note 3.
10Supra Note 2.