Data and Artificial Intelligence (AI) are not just technological advancements or buzzwords – they are systematically reshaping the core dynamics of modern businesses. Last month we hosted our annual panel event where industry leaders from Calgary gathered to discuss a pivotal topic: the intersection of data and AI and its transformative impact on workforce development.
To prepare the room to be on the same page for the discussion we began the evening with an in-depth presentation on the history of AI and how it works, led by Ambyint CTO, Ferdinand Hingerl. When educating attendees on how generative AI works he shared a humorous anecdote about his father to help explain, “My dad recently learned cooking. So far he can do two things – eggs sunny side-up and eggs over medium. So the hope is, for my mom at least, that at some point he will make something else because he now knows how to work with different types of eggs, how to generate different kinds of outputs, and eventually be able to do something like an eggs benedict. Basically, he learned patterns – we hope he will get creative and make something new. That’s similar to how generative AI works.”
Once the room was up to speed on AI basics, the panel — led by expert moderator, Kelsey Hahn, Co-Founder & CEO of Monark — dove into the core of the discussion.
Tackling the Introduction and Application of AI in Business Processes
When introducing AI into business processes, the approach typically begins with identifying key business challenges that are difficult to solve through traditional methods. Organizations should first focus on pinpointing specific problems where AI can provide substantial value. This involves a thorough assessment of business needs and the potential impact of AI solutions.
Shelley Ralston, CHRO for AltaGas, discussed the concept of “covert disruption,” where AI is used to solve business cases in innovative ways. Ralston provided an example involving their regulatory team, which faced a daunting task of preparing high-stakes regulatory submissions. By partnering with the company’s digital team, known as the “Triple A Team” (Analytics, Automation, and AI) they developed an AI solution called “Kelly AI.” This AI system processed vast amounts of regulatory documents, significantly reducing preparation time and saving substantial costs. But more importantly, it also allowed the legal team to focus on higher-value work, such as analyzing insights and preparing for case scenarios.
She stressed the importance of developing a strong narrative around AI initiatives to ensure their success and scalability. It’s crucial to foster a culture of innovation and openness among employees. Engaging the workforce in AI implementation process helps ensure that the technology is effectively integrated into daily operations. “It’s not just about how much money we saved and how much time,” Ralston says. “It’s that we’re getting these team members excited about doing the higher value work instead of spending six months trying to find information.”
Maintaining a strong focus on continuous improvement and scalability is essential. AI initiatives should be regularly evaluated and refined to ensure they continue to meet business needs and deliver value. “It’s our job as leaders to continue to not let that go away,” Ralston stated. “It’s like R&D — an area where we say, ‘do we want to spend the money or not?’ We need to make sure that we protect it, but also nurture and feed it so it doesn’t just sit there stagnant.”
Building Internal Capabilities vs. Outsourcing
With AI adoption ramping up quickly across nearly every industry, executives face several challenges and opportunities when deciding whether to build internal AI capabilities or outsource to third-party providers.
Building internal AI capabilities offers the advantage of tailored solutions aligned with organizations’ specific needs and culture. However, it poses challenges in terms of resource allocation, skill acquisition, and maintaining competitive edge in rapidly evolving AI technologies. On the other hand, outsourcing to third-party providers can provide access to specialized expertise and resources, accelerating AI implementation. Yet, it may entail risks such as loss of control over sensitive data, dependency on external vendors, and potential conflicts of interest. Executives must carefully weigh these factors to determine the most suitable approach that aligns with their strategic objectives, organizational culture, and long-term sustainability.
Colleen Pound, CEO & Founder of Proxure, emphasized that AI adoption is primarily a people issue, with significant challenges including existing capacity constraints and capability constraints and the ability to train and sustain (to keep up to date) on AI initiatives. She noted, “You don’t know what you don’t know, and you don’t necessarily have the expertise to know what good looks like or how to apply it.” Highlighting the difficulty of building internal capabilities (the time and cost to upskill, having an educated user base) without the necessary expertise.
“The opportunities are vast if done correctly” she added. “To do way more with way less, way better, the ability to leverage insights, to enhance customer experience, to make better data driven business decisions when it comes to cost, quality, efficiency and productivity and to learn how to predict the future with some reasonable certainty and gain an advantage.”
Shesta Babar, a People & Change leader from KPMG, added that executives should not view AI as an entirely foreign concept, but rather as an extension of their existing workforce strategies. She suggested, “When you face capacity or capability constraints, you must make critical decisions around your workforce and the best way to achieve your intended goals. These decisions include ‘do we buy, do we borrow, do we build’ our talent — I think it is the same concept here with AI. We need to view it as a tool that serves as a cognitive enablement tool not a replacement.”
Building on the other panelists’ thoughts, Dr. Banks Odole — Academic Chair, Data Portfolio and AI at SAIT, pointed out the potential for AI to enhance creativity and skill development within organizations. He explained that AI can enable employees to learn new skills and improve their workflows. “AI can significantly change the way we work, enabling new skills and enhancing creativity,” Odole shared. “As leaders, we must be prepared for these changes and ensure we are ready to adapt and integrate these tools into our organizations.”
Ralston summed up the conversation by encouraging executives to shift their focus from cost-savings to value creation. She highlighted that, “As executives, it’s our job to start pushing the conversation. How can we create better value?” By fostering a culture of continuous improvement and innovation, leaders can ensure that AI initiatives are not only implemented, but also sustained and scaled effectively within their organizations regardless of if they’re built internally or externally.
Safeguarding Data Privacy and Security in AI Adoption
As organizations increasingly rely on AI the volume of sensitive data being handled has surged. Ensuring the security of your company’s data is not just a technical necessity, but a fundamental aspect of maintaining trust. Data breaches and privacy violations can lead to severe financial penalties, reputational damage, and loss of stakeholder confidence. Safeguarding your company’s data is essential to sustaining a competitive advantage and fostering long-term organizational resilience.
Odole cautioned executives to take a step back and understand their infrastructure framework, governance policies and potential exposures before rolling out these solutions en masse. “There are so many technologies out there that will give you what you want,” Odole explained. “But the best is what’s right for you and often times that’s based on your infrastructure and exposures.”
Balancing risk and compliance with innovation in AI adoption is a critical challenge for executives. Executives must find a balance that allows the organization to explore and leverage AI’s potential while maintaining robust security practices. This involves integrating risk management into the innovation process, ensuring that new AI initiatives are evaluated for potential security and compliance impacts from the outset.
Babar likened the balance executives should take when evaluating AI adoption with the risk management she takes for her children, “I want my children to be creative and have fun,” she explained. “But if fun gets in the way of their safety that’s a concern for me. I want to put up enough guardrails where my kid is safe but has the creative liberty to learn. Similarly, I think that’s where you’re going to strike a balance of not trying to overcomplicate compliance so that you’re stifling people but also protecting your organization from getting hurt.”
Fostering a culture of security awareness within your organization can empower your workforce to be vigilant and proactive in safeguarding data. While adopting a proactive and integrated approach to risk management can foster innovation without compromising data security.
AI Adoption is Built on Trust and Corporate Readiness
Benjamin Kemp, CEO of Ambyint, shared a compelling case study highlighting the transformative impact of AI and data analytics in the oil and gas sector.
Kemp explained that Ambyint processes over 15 million data events per day to support 7,500 wells across North America. This massive data handling capability enables the company to provide real-time, automated solutions that allow customers to focus on the most critical issues. As Kemp put it, “Our users are typically responsible for overseeing the production of dozens, hundreds, or even thousands of wells each. They simply don't have enough time in the day to effectively monitor every well. With our platform, they can now optimize every well, every day, ensuring they can focus their attention on the most critical issues."
Initially, there was reluctance to adopt AI-powered solutions without human oversight, as many were wary of disrupting their core business processes. However, through increased transparency and a focus on trust-building and change management, customers began to recognize the value of implementing an AI solution, like Ambyint. “Our platform enhances workforce efficiency and production with advanced analytics, anomaly detection, and automation,” Kemp shared. “Daily reports provide critical insights and transparency. Our AI-powered solution quickly identifies critical issues, reducing resolution time. Now, companies are increasingly automating their processes to optimize well performance and boost productivity.”
Kemp also emphasized the importance of assessing a company’s readiness for change. “Companies that are already undergoing a digital transformation may be able to implement AI solutions more effectively,” he noted, “leading to substantial improvements in operational efficiency and workforce productivity.”
The impact on employees has been profound. Engineers who were initially skeptical now speak highly of how AI has transformed their work, enabling them to focus on complex problem-solving rather than routine tasks. Kemp highlighted that, thanks to the insights provided by Ambyint, engineers can now tackle more important tasks. “They consistently express how Ambyint has made their workloads more manageable and improved their efficiency.”
Navigating the Future with Data and AI
The discussions that emerged from our panel event showcased the profound impact of data and AI on workforce development and business processes. The journey to effectively harness AI is multifaceted, involving technological, strategic, and cultural dimensions. The potential of AI to drive efficiency, innovation, and competitive advantage is evident. However, organizations must remain vigilant about the associated risks — especially around data privacy and security. Balancing these security measures with a commitment to innovation ensures that businesses can explore AI’s full potential without compromising on compliance and risk management.
The path forward involves integrating advanced AI tools and shifting organizational mindsets. Fostering a culture of continuous improvement and readiness for change is essential. Trust from leaders and employees is crucial — trust that AI will make their work easier and more rewarding without eliminating the need for a human workforce. By embracing AI as a tool for enhancing creativity, skill development, and value creation — not merely for cost savings — executives can lead their organizations through the complexities of digital transformation.
“We stand on the cusp of a new era defined by AI and data,” says Agilus CEO, Craig Brown. “The future of work is not just about adopting new technologies but about creating an environment where our teams can thrive and innovate. By harnessing the power of AI, we can unlock new opportunities, drive continuous improvement, and ensure that our workforce is equipped to meet the challenges of tomorrow.”
For nearly half a century, Agilus has been dedicated to connecting talented individuals with meaningful employment opportunities in diverse roles across Engineering & Technical Trades, Technology, and Office Professional sectors. Our deep understanding of the Canadian market, combined with the extensive expertise of our nationwide team members, allows us to lead with genuine human connections and deliver better outcomes for both our clients and candidates. Contact us today to discover how Agilus can transform your world of work.
