AiThority Interview with Nicole Janssen, Co-Founder and Co-CEO of AltaML

Hi Nicole, welcome to our AiThority Interview Series. Please tell us about your journey so far as a seasoned technology expert. How did you start at AltaML?

Our journey has been a continuous learning curve. My early career was not in tech so being referred to as a “seasoned technology expert” still makes me laugh!

However, I use that to my advantage as I lean into helping our partners and clients understand the opportunities that come from AI but in a language that makes sense to them. While we wish we had a crystal ball to predict our successes or failures, the reality is that no one knows exactly how a business venture will unfold. However, what we did recognize early on was the potential of entering the AI space to disrupt the industry, and taking that bet on ourselves has proven to be a game-changer. Throughout this journey, we’ve embraced adaptability, listened to our customers, taken calculated risks, and remained committed to innovation with the support of our team, but the journey isn’t over yet. We’re continually researching, ideating, and striving to be leaders in this space. This pursuit is ongoing; just when you feel like you’ve caught up, there’s a shift. It’s this constant evolution that makes every day interesting.

Please tell us more about AltaML. What are your core offerings?

We operate with two sides to our business: Services and the Venture Studio. On the Services side, we leverage specialized knowledge to build custom AI solutions for enterprises and public sector clients. These relationships and exposure to problems help feed opportunities for the other side of the business. The Studio allows us to identify desirable market opportunities and build a portfolio of industry-specific ventures that build AI products.

Our goal is to provide organizations with access to the latest AI technologies and education to support adoption throughout all levels of the organization with ethical implementation. We operate across various sectors, disrupting traditional industries including agriculture, health, financial services, energy, and resources. We have a deep understanding of organizational challenges which helps us co-develop customized solutions. We’re extremely proud that once our solutions pass feasibility, 70% of them move toward operationalization, this is well above the industry standard.

Nearly half of Americans are using digital assistants. What is your take on AI-powered tools such as chatbots and virtual assistants?

With the inevitable rise in AI usage, it’s crucial to provide people with the tools for informed education and adoption.

As industry leaders, our commitment extends beyond technological advancement. Recognizing the profound impact these tools have on daily lives, we prioritize alignment with our values of transparency, privacy, and security.

Our focus isn’t solely on pushing boundaries; it’s about doing so responsibly. These tools play a vital role in societal advancement and they show great potential. While incredibly helpful, they also highlight the need for human involvement during their development and deployment. End-users need to understand how these systems store and manage critical data.

What does the AI adoption journey look like with AltaML for enterprise software?

AI is transformative, and while most are exploring its possibilities, it’s important to know that operationalizing AI is hard. We’ve been at this for six years now and of the metrics we follow most closely is the percentage of use cases we work on that pass the initial feasibility test and move toward operationalization.

These are some of the lessons we’ve learned along the way:

1. Start with real business problems, not just AI novelty
2. Prioritize AI initiatives strategically, comparing use cases
3. Begin small to build momentum and cultural change
4. Involve data science early to assess feasibility and inform strategy
5. Integrate AI into overall company strategy, not just IT
6. Address concerns about job displacement by engaging end-users early and emphasizing change management

Don’t be afraid to kill things fast.

We encourage companies to compare use cases and set a prioritized roadmap, rather than evaluating them one by one. Engage the end-user early in the development process to foster their involvement and become change champions for the organization. Plan for change management, which may take two to three times as long as building the tech but is necessary for successful adoption.

The NLP market is predicted to be almost 14 times larger in 2025 than it was in 2017, increasing from around three b****** U.S. dollars in 2017 to over 43 b****** in 2025. What are your comments?

The prediction that the NLP market will grow to over $43 b****** by 2025 is a strong indicator of the impact it’s having across numerous industries. The field is evolving beyond just natural language to become truly multimodal, encompassing vision and audio comprehension as well. This isn’t merely growth; it’s a transformation, driven largely by advancements in large language models. These models are reshaping how we understand and interact with information, representing a paradigm shift in technology and enabling multiple new use cases that were previously unachievable.

We’re at the forefront of this change. In partnership with major hyperscalers, we are actively delivering innovative solutions that harness the power of advanced generative AI to address real-world challenges.

As we push the boundaries of what’s possible with AI, we are equally committed to responsible innovation. There are significant challenges and risks associated with this technology. For us, it’s about ensuring that these powerful tools enhance human potential and operate transparently and ethically. This commitment influences every project we undertake and is a cornerstone of our partnerships with industry leaders. We’re not just building technology; we’re shaping the future of how technology is created and consumed with responsibility at its core.

With the growing importance of responsible AI, how does AltaML approach ethical considerations and bias mitigation in the development and deployment of AI solutions?

First of all, responsible AI is non-negotiable for us. As a company, we approach ethical considerations and bias mitigation in AI development and deployment with a firm commitment to responsible practices. We implement robust controls, adhere to established policies, and prioritize education and awareness.

Embracing responsible AI fosters a culture of shared responsibility, enhancing our reputation and attracting top talent. Canada has the potential to lead in responsible AI, but it requires collaboration among academia, government, and industry, as well as effective regulation that balances innovation and protection against harm.

Our projects start and end with ethical practices, ensuring bias is removed and risks are mitigated or kept manageable within the team.

What AI initiatives are you currently focusing on revolutionizing health care delivery?

Within our Talent Accelerator program, GovLab—an innovation hub for public sector organizations. We’ve recently welcomed a new Tenant focused on improving health outcomes for Albertans. Though in its early stages, this partnership holds promise for revolutionizing healthcare delivery. We’re exploring various use cases, including workforce planning for health care workers. For instance, we’re collaborating with Cancer Care Alberta’s Precision Analytics team to develop a model predicting anticipated workloads, informing resource allocation within Cancer Care with the expected outcome of reducing wait times for patients.

How does AltaML’s AI-powered solution enable manufacturers to chart a course of data-driven excellence and thrive in a competitive and evolving global market?

From the outset, we’re committed partners, collaborating closely to co-develop AI solutions tailored to our clients’ specific needs.

We iterate fearlessly to ensure optimal output, fostering thriving solutions in the fast-paced global market. This support spans every stage, driving increased efficiency, improved decision-making, enhanced productivity, and ultimately, greater profitability for our clients, partners, tenants, and the entire ecosystem.

What are the biggest challenges and opportunities you see in leveraging machine learning to solve real‑world problems?

As someone deeply invested in technology, I believe there are both challenges and opportunities when it comes to using machine learning to tackle real-world problems. One of the biggest challenges we face is ensuring that we use AI ethically and responsibly, taking into account issues like bias and privacy. Plus, the tech landscape is always changing, so we need to stay innovative and agile to keep up.

But amidst these challenges, there’s so much potential.

Machine learning has the power to change entire industries by automating tasks, streamlining processes, and uncovering insights from data like never before. It allows us to create personalized solutions that make a real difference in people’s lives, boosting efficiency and effectiveness across the board. By facing challenges head-on and by seizing opportunities, we can unlock the true potential of machine learning and make a positive impact on society. It’s about embracing the possibilities without letting the fear of risk hold us back.

As AI adoption continues to accelerate across industries, how does AltaML envision the future of AI-powered innovation, and what role do you see your company playing in shaping that future?

In the time we’ve been fully immersed in this space, significant changes have already occurred. While it’s challenging to predict the long-term future, we’re committed to remaining actively engaged, guiding decisions, advocating for responsible production, and nurturing the growth of future tech talent.

Leadership opportunities abound globally, and Canada must assert itself boldly, showcasing our capabilities to the world. Despite our strengths in innovation, research, and talent, there’s a sense that we’re lagging. My hope for the future lies in regulations that support rather than hinder innovation, thereby propelling Canada’s AI advantage forward.

Collaboration and partnerships are key in the AI landscape. How does AltaML foster strategic alliances and ecosystem relationships to enhance its AI offerings and expand its market reach?

We’re committed to the power of collaboration and partnerships in driving progress within the AI landscape, all while avoiding silos.

By forging purposeful relationships with industry leaders, academic institutions, and government bodies, we strengthen our AI offerings and expand our market reach. Together, we combine our strengths, share knowledge, and create innovative solutions that make a real impact. Through these partnerships, we not only enhance our capabilities but also reach more people and drive meaningful advancements in AI adoption and application across various sectors.

Ultimately, it’s about coming together to build a better future with AI.

Thank you, Nicole! That was fun and we hope to see you back on AiThority.com soon.