Using AI to bring value to organizations | Connie L. Braun and Juliana Saxberg

By Connie L. Braun and Juliana Saxberg ·

Law360 Canada (April 10, 2024, 9:16 AM EDT) --
Connie Braun
Connie Braun
Juliana Saxberg
Juliana Saxberg
For every risk inherent in AI adoption, there is a counter-argument that AI has the potential to unlock benefits and solve real-world problems that have heretofore eluded human capability. Machine Learning technologies are already recognized to be advancing medical research and patient care, improving decision-making, mitigating climate change and distributing food aid more effectively, among other benefits.

Some analysts suggest that any Canadian businesses and entities that resist the adoption of AI technologies are putting themselves at a competitive disadvantage that will be difficult to remedy. The investment needed to “catch up” to competitors using AI will be so great that it becomes unaffordable. For both human and organizational factors, falling behind on the AI learning curve may make catching up impossible as the technologies continue to progress. On a global level, there is a larger risk: not meeting the challenge of effective AI risk governance will prevent the development of solutions that are needed to ensure a viable future for the planet and humankind.

A recent IBM Canada report states that Canadian businesses are adopting AI, investing in people and technology, and seeking opportunities to transform critical industries and ways to deliver value while developing and implementing governance that is sound and responsive. To be most effective, businesses will need to focus on creating learning and development plans that both require and help employees upskill or reskill to use the AI technology successfully. Without this investment in people, any investment in AI technology will be wasted.

Today, need is driving the adoption of AI to automate repetitive processes and improve productivity with AI already found in many off-the-shelf business applications. At the same time, there are barriers to the adoption of AI for many entities. These barriers include the cost of upskilling or re-skilling employees, lack of confidence in the transparency and trustworthiness of AI and discomfort with compliance risk as governments and regulators race to put rules into place.

AI is here to stay and even now is proving that it is reshaping industries and societies. For this reason, building strong and thriving AI technologies for use in Canadian businesses is imperative for success. This means that all must safely and ethically use generative AI. Ensuring high-quality data streams and protecting against data poisoning must be prioritized in development cycles, to guarantee that AI remains trustworthy. Having an easily understood AI framework accompanied by enforceable governance and oversight will allow businesses to build, introduce and bring generative AI applications to market responsibly.

One key barrier to AI adoption by Canadian organizations is finding specific use cases for AI tools to tackle and support business-critical challenges. Taking advantage of this opportunity remains a bottleneck. Getting beyond it continues as a crucial first step for many businesses as leaders look for ways that generative AI can solve specific problems and support strategic priorities, thus bringing value to businesses. This is one area where collaboration among governments, regulators and businesses could move the needle by removing compliance confusion and barriers. Rather than focusing exclusively on the risks of AI adoption, stakeholders need to demand critical conversations with policymakers to guide the development and evolution of generative AI without squelching innovation and growth. Canadian businesses and lawmakers can master this challenge, thus allowing Canada to become and continue as a global leader in responsibly leveraging the potential of generative AI.

Deloitte’s 2023 report on Canada’s AI ecosystem reveals that Canada has more than 600 businesses currently active in AI, placing Canada in the top five countries with the highest number of companies using generative AI. Financial support for the development and deployment of AI applications, innovation in cloud computing, software engineering, scaling large language models, processor (chip) design and manufacturing, machine learning and quantum computing are quickly removing barriers that have stalled AI development in the past. With these advances coming so rapidly, generative AI is poised to explode in usefulness, popularity and affordability.

Different industries will, of course, use generative AI differently. For some, the value will be evident in the ways that their operations become more efficient at accomplishing routine tasks. Other businesses will use reinforcement learning and robotics to reduce backlog. Some will use generative AI to promote a more inclusive system that will help to break down barriers to education in scientific and technical fields. Still others will focus on accelerating the journey toward profitability, thus competing more effectively in the global economy. The list goes on.

Generative AI can work as a fast-acting upskilling technology with powerful tools that improve productivity. Much of the infrastructure is already in place, especially related to electricity. The big challenge here is the electrical footprint needed by generative AI. Some businesses will require retooling to see progress toward the achievable goals of reducing time, effort, expertise and expense. Gradually, generative AI will significantly change how businesses perform their most important tasks and achieve success. Failing to get on board and waiting to see how generative AI develops is not an option.

If you are still doubtful, try your own research on how generative AI could be applied in your organization. Decide which model(s) should be adopted to the greatest benefit. Then, get busy deploying generative AI to improve specific tasks, business processes, interactions with customers and more.

By continuing to lead in development, success and productivity with generative AI, Canada’s further investment in the advances and skills that make new opportunities possible will continue. Prioritizing smart, principles-based legislation to govern the use of AI will go a long way toward ensuring that technologies using AI will successfully deliver positive social and economic benefits.

Connie L. Braun is a product adoption and learning consultant with LexisNexis Canada. Juliana Saxberg is a practice area consultant in corporate and public markets with LexisNexis Canada.
 
The opinions expressed are those of the author(s) and do not necessarily reflect the views of the author’s firm, its clients, Law360 Canada, LexisNexis Canada or any of its or their respective affiliates. This article is for general information purposes and is neither intended to be nor should be taken as legal advice.


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