Reaping the Rewards of AI: Transforming Business Responsibly

Artificial Intelligence (AI) is reshaping industries, creating new opportunities for businesses to innovate, streamline operations and enhance customer experiences. For small and medium-sized enterprises (SMEs), particularly those led by women entrepreneurs, AI offers a chance to bridge gaps and thrive in competitive markets. Leveraging AI tools responsibly can help accelerate growth, increase visibility and level the playing field in adopting technology tools because the gender gap in AI adoption is narrower than with other technologies. This is important because women are 51% of the workforce and women are majority owners of almost 20 percent of private sector businesses. The 2025 State of Women’s Entrepreneurship in Canada research by the  Women Entrepreneurship Knowledge Hub (WEKH)  found that women-owned businesses are less likely to adopt emerging technologies like AI, with an adoption rate of 12.3% compared to 16.5% among men-owned businesses. However, generative AI tools are gaining ground. Additionally, businesses with majority women ownership demonstrate the highest overall innovation rate at 38.0%, significantly outperforming businesses with no women ownership (25.6%).

Artificial intelligence for SMEs was the focus of the presentation by Wendy Cukier, founder of the Diversity Institute (DI) and academic research director of the Future Skills Centre (FSC) at the 2025 StrikeUp conference. The event attracted more than 3,000 registrants and Cukier spoke about the transformative potential of AI and the importance of adopting it responsibly. “AI offers entrepreneurs and small businesses opportunities to transform their operations by driving efficiency, innovation and cost reductions,” Cukier said. While Canada leads in AI research and development with pioneers like Nobel Prize winner Geoffrey Hinton and Yoshua Bengio driving global advancements—it lags in adoption, with 35% of Canadian businesses currently using AI, compared to nearly 72% in the US.

AI for Small and Medium-Sized Enterprises

For SMEs, AI offers transformative opportunities across the entire value chain—from automating tasks to enhancing customer service—driving efficiency and productivity. Women entrepreneurs in Canada are well-positioned to benefit: in 2020, women-owned businesses generated $90 billion in revenue, employed nearly 1 million people, and outpaced others in innovation while matching export levels. Encouragingly, the AI gender gap is narrower than in other tech areas, with 47% of women familiar with AI tools compared to 53% of men—good news for women-led SMEs looking to adopt and lead in AI.

“The way AI allows for personalization is really transformational,” Cukier said. Artificial intelligence, like ChatGPT, can analyze large datasets, offering SMEs insights to improve decision-making and identify market opportunities. For example, applications like QuickBooks, Salesforce Einstein and Jasper enable resource optimization and informed strategic planning. By integrating AI into everyday operations, businesses can innovate, reduce costs and expand capabilities. However, Cukier highlighted the importance of data quality and precision in using AI effectively: “The more specific the prompts or instructions you give, the better the outcomes you get. Good prompts are clear and specific.” Building AI skills, such as prompt engineering, allows SMEs to achieve more accurate and impactful results. Quality assurance, detailed context and clear instructions—including examples and desired formats—are critical to success. 

Risks Associated with Artificial Intelligence Use

She pointed to a recent report by DI, the Environics Institute and FSC, that highlighted the urgency for employers to create policies and implement training on using AI tools in the workplace because employees are not waiting for their employers to provide the necessary training. “Employees are already using AI, even if employers aren’t aware of it,” Cukier said. While both large and small businesses acknowledge the growing need for AI skills, many employees are left to navigate AI tools independently— ​​nearly three in ten employed Canadians are using AI tools in the workplace, but almost half (44%) of those employees using AI have not received any formal training. And, almost three-quarters (68%) of those who used AI at work are doing so on their own – either  they are learning to use the tools without any training (44%) or they are using the tools with self-guided training (24%).

While AI offers immense potential, it also comes with notable risks. Bias and discrimination can arise when algorithms perpetuate biases in their training data, leading to unfair outcomes. “AI is only as smart as the information it has access to, and if it only has access to biased information, it will produce biased results,” Cukier said. Data privacy is another major concern, as AI systems rely on vast amounts of sensitive information, creating potential vulnerabilities. Another risk lies in AI’s lack of transparency, which makes it challenging to understand how decisions are made and to identify potential errors or biases. “ChatGPT, for instance, can make things up,” noted Cukier, referencing issues like misinformation and reputational risks. Finally, AI systems face security challenges, including cyberattacks and compliance with evolving regulations, posing risks for SMEs. Despite these concerns, understanding and mitigating these risks is crucial for leveraging AI responsibly.

Building Guardrails for Responsible Artificial Intelligence Use

Building robust guardrails for responsible AI begins with embedding ethical principles and governance frameworks into AI systems. These guardrails ensure that values such as fairness, transparency, accountability and privacy are upheld throughout the development and deployment processes. By prioritizing these values early, organizations can mitigate risks such as biases, discrimination and non-compliance with regulations. “Think of some of these tools as assistants,” Cukier noted, emphasizing that AI can augment human efforts while requiring robust quality assurance and controls. A human-in-the-loop approach is another key component of responsible AI adoption, ensuring oversight and reducing errors or unintended biases. 

The Diversity Institute has developed an AI literacy framework. Cukier outlined different levels of AI skills: deep AI skills, which involve knowledge of AI development frameworks and machine learning models; mid-level AI skills, which include competence in using generative AI technologies like ChatGPT or Microsoft Copilot for content generation, analysis, and problem-solving; and basic AI literacy, which involves familiarity with generative AI tools along with awareness of key ethical considerations like bias and privacy. While not all workers need deep AI skills, Cukier emphasized that building AI literacy across all levels of an organization is essential.“We need workers with deep technology skills with backgrounds in science, technology, engineering and math (STEM), but more importantly, we need people to be able to lead a company’s digital transformation.  Regardless of the business you have or plan, everybody needs basic AI literacy,” Cukier explained. Programs like Advanced Digital and Professional Training, Google’s and Microsoft’s training courses can provide foundational to advanced AI skills. Matching AI tools to business needs ethically ensures that companies optimize their potential without inadvertently creating problems.

To close, Cukier encouraged organizations to “think about the potential of AI for your business needs, test applications, and prioritize training,” while applying a diversity and inclusion lens to AI processes. Staying informed about trends and evolving regulations will help organizations remain competitive and responsible in the AI era.