Embracing AI: Strategic integration and industry impact

In this extensive interview, we talked about the growing adoption of artificial intelligence in the business world, the necessity of skill development, and its strategic implementation in business. Hanna also addresses the impact of EU regulations on competitiveness, the hype surrounding AI, advocating for thoughtful and effective applications rather than indiscriminate use.  

Hanna: Siili holds a distinctive position, especially in building B2B digital solutions. We were among the first in Finland to develop self-service portals for B2B and manufacturing companies, which already sets us apart. Our approach to AI-powered development gives us another edge. 

Q: So, can you explain Siili's approach to AI development and how it differs from what others do? 

Hanna: Certainly. We see AI as a holistic capability. At Siili, AI isn't just another product or a standalone offering; it’s embedded into everything we do. This means every part of our operation, whether consulting or internal management, utilizes AI tools daily. This not only enhances our efficiency but also allows us to constantly refine our methods and offerings based on real-time insights and feedback. Our developers, designers, and data engineers continuously adapt and learn to apply AI in their projects, ensuring our solutions are innovative and practical.

So, we eat our own dog food. We are becoming AI-powered across all our internal functions, from finance and HR to marketing. Additionally, we aim to embed AI-powered design and development into all our customer projects.  This comprehensive integration helps tailor our solutions uniquely to each client’s needs. Every part of our operation, whether consulting or internal management, utilizes AI tools daily. This not only enhances our efficiency but also allows us to constantly refine our methods and offerings based on real-time insights and feedback. Our developers, designers, and data engineers continuously adapt and learn to apply AI in their projects, ensuring our solutions are innovative and practical. 

Q: How does this integration of AI benefit Siili’s clients? 

Hanna: By embedding AI deeply into our operations, we ensure that our clients benefit from the latest in AI technology, tailored specifically to their needs. This isn’t just about automating routine tasks; it's about enhancing decision-making, optimizing operations, and fostering innovation within their businesses. Our clients see real improvements in efficiency and strategic insights, which can be a game-changer in competitive industries. 

Q: From your perspective, what have been the market changes since the AI boom two years ago? And How has the interest in AI developed, particularly in the Nordics? 

Hanna: In Finland and the Nordics in general, there has been high curiosity towards artificial intelligence and machine learning. However, despite the early interest, studies indicate that most companies are just beginning their journey in AI adoption. It’s 2024 now, but the transformation is far from complete. Gaming companies like Supercell are highly advanced, embedding machine learning deeply into their operations. Yet, there are many companies that are not so digitally native are are lagging behind in AI investment compared to Swedish companies 

Q: Do you feel there's a need to push AI projects to clients, or are they readily embracing AI? 

Hanna: Most clients are cautious. For instance, Silo.ai conducted a study revealing that investing one million euros in AI is surprisingly rare in the Nordics. AI adoption isn't a quantum leap; it's more incremental: more PoCs, more AI-powered solutions, and then more MLOps in production. Also, the push needed isn't just technical—it's about skills, and upskilling is really needed. The big platforms may come from China or the US, but here in Europe, we need to train our people to be top-notch in this field. Europe or Nordics are not leading this technologial revolution. 

Q: What’s businesses’ general attitude towards AI? There seems to be a significant hype around AI solutions. 

Hanna: It’s a common trend that companies think they need AI everywhere. But eventually, they learn where it fits best. We're learning to use AI where it makes sense, and over time, it becomes embedded and routine in all operations. The real value of AI comes in automating repetitive tasks and enhancing complex decision-making processes. For instance, while AI can help streamline code documentation or manage test cases, it's not as effective in generating code from scratch without precise instructions and rich context, but of course this can change over the time. The goal is to use AI to free up human talent for more complex, strategic tasks requiring nuanced thinking and creativity. 

Q: So, do you think businesses tend to be overeager to adopt AI at any cost without understanding its applicability? 

Hanna: Absolutely. There's a sort of 'hammer phase' happening where every problem looks like a nail when you're holding AI. This mindset leads to the belief that AI is the solution for everything, which is not the case. It’s essential to understand that AI is a tool, and like any tool, it’s great for certain tasks but not for others.  AI should be seen as a support that optimizes processes and enhances productivity, not as a replacement for human ingenuity. We hope to reduce the time spent on mundane tasks significantly, allowing our teams to focus on enhancing product quality and innovation. Ultimately, AI should empower us, not constrain us. We are in a learning phase, using AI everywhere until we figure out where it works best. It’s important to recognize where AI is actually beneficial and not just follow the hype blindly. 

Q: With Siili positioning itself as a truly AI-powered software agency, do you see the ultimate goal for businesses to build their own AI competencies, or is outsourcing still a significant component? 

Hanna: Right now, it seems many companies, especially the larger ones in Finland, are indeed building their own data science teams. They've been doing this for years. However, there are aspects, particularly related to data preparation and formatting, that are effectively outsourced. Outsourcing can help streamline operations by ensuring that data scientists receive data in the right format at the right time, which is crucial for efficiency. Consulting remains vital; it helps companies understand the best AI solutions to implement, which is often more complex than simply having the capabilities in-house. 

Q: Regarding AI integration, do companies prefer building in-house AI-competent teams or outsourcing? 

Hanna: Currently, most large companies in Finland have their own data scientist teams. Outsourcing might be suitable for specific tasks like preparing and delivering data in the right format for data scientists. However, we also need consultants to help businesses understand the optimal AI solutions to pursue. 

Q: How do you see the role of AI evolving in business strategies? 

Hanna: AI will likely become a mandatory part of business infrastructure, similar to how digital solutions are today. For example, recommendation engines in e-commerce platforms are the standard now, and not having one is a significant disadvantage. And then, another example could be a travel agency that doesn't have the recommendation engine competing with one that does. Which one would you use? The same will eventually happen with AI – not integrating AI in some way will, at some point, be seen as lagging behind the curve. It's about enhancing efficiency and staying competitive and delivering a tailored experience.   

Q: What impact is AI having on the IT job market right now? 

Hanna: AI is significantly impacting the job market by creating a high demand for new skills and roles. Companies that integrate AI into their operations are seen as more attractive employers because they offer opportunities for learning and advancement in cutting-edge technology. This shift is not just about adopting new tools but also about transforming business models and operational strategies. 

Q: What are the new roles that are emerging because of AI? 

Hanna: Beyond traditional roles like data scientists and data engineers, we are now seeing a rise in specialized positions such as Machine Learning Operations Engineers, Machine Learning Engineers, and Analytics Engineers. There’s also a growing need for full-stack data scientists who can handle a range of tasks from data preparation to model deployment. These roles reflect a deeper integration of AI into various business processes. 

Q: How are companies adapting their hiring strategies to accommodate these changes? 

Hanna: Companies are increasingly seeking to build these capabilities in-house. They are not only hiring AI experts but also training existing staff to understand and leverage AI technologies. This internal development is crucial for companies to maintain a competitive edge, as it ensures that their workforce can handle AI-driven tasks and projects effectively. 

Q: What should professionals do to stay relevant in this AI-driven job market? 

Hanna: Professionals should focus on continuously updating their skills in both AI and domain-specific knowledge. Engaging with ongoing education, whether through formal courses, workshops, or self-study, is essential. Understanding the implications of AI in their field and being able to work alongside AI tools will be key differentiators for any professional moving forward. 

Q: How should companies approach building these capabilities internally? 

Hanna: Companies need to invest in training and developing their current workforce while also attracting new talent. This might involve partnerships with universities, involvement in tech communities, or creating internal accelerator programs to nurture the required skills. It’s crucial for companies to be proactive in shaping their talent pool to keep up with the pace of AI adoption. 

Q: Looking forward, do you think there will still be a need for developers who aren't versed in data and AI? 

Hanna: The role of traditional developers is changing. While there will always be a need for certain types of development skills, the future belongs to those who can bridge the gap between traditional software development and AI-driven technologies. Developers who understand data and AI will be better positioned to innovate and lead in their fields. It’s not just about understanding algorithms but also about how those algorithms can be applied effectively in a business context. 

Q: So these roles are becoming the most sought after at the moment? 

Hanna: Yes, they are in high demand because the journey into AI is just beginning for many sectors. Those who can not only develop system landscapes but also understand machine learning and analytics are particularly valuable. Companies need more than just AI experts; they need professionals who can integrate AI into broader business processes from the ground up. There is a need for a combination of development skills and deep understanding of data analytics and machine learning. It's about more than just coding; it's about building reliable, validated, and trustworthy solutions. These roles require a blend of technical expertise, critical thinking, and strategic insight to ensure the data used is appropriate for the AI solutions being developed. 

Q: Is there a challenge in finding people with these integrated skills? 

Hanna: Absolutely, there is a significant gap. The ideal candidates are rare because these skills are just emerging as educational institutions and training programs are beginning to adapt to these new needs. This rarity makes such individuals highly valuable and sought after. 

Q: In terms of organizational structure, how is AI influencing changes? 

Hanna: AI is driving organizations to rethink their structures. With the introduction of roles like AI strategists and ethicists, companies are embedding AI deeply into their strategic layers, not just their technical teams. This restructuring is aimed at better aligning technological capabilities with long-term business goals and ethical considerations, ensuring AI is used responsibly and effectively across all operations. 

Q: What challenges, in your opinion, do companies face in adopting AI? 

Hanna: The main challenge isn’t just about adopting new technologies but integrating them meaningfully into existing systems and processes. Companies must understand the value AI brings before making substantial investments. 

Q: What are your thoughts on AI's future in business? 

Hanna: As AI tools and applications become more integrated into daily operations, they’ll transform how we work, making routine tasks more efficient and allowing us to focus on more complex issues. It’s an ongoing journey, and continuous learning and adaptation are key. 

Q: What do you think will be the impact of European regulations around data and AI? Are you concerned about the business impact here? Do you think it will change how the game is played? 

Hanna: Definitely, the impact will be significant. Let's start with the positives: the AI Act that the EU has been planning for years has evolved significantly. It's designed to secure personal data and ensure it cannot be used indiscriminately, unlike the practices seen in the US and China. This respects individual privacy and personal space. However, there are downsides, notably the additional costs and complexities these regulations introduce for businesses in Europe. 

Q: So, what are the negative implications of these regulations? 

Hanna: The main challenge is that these regulations may increase operational costs for European companies, making it harder to compete globally. Additionally, only a small percentage of technological giants are based in Europe—about 4%. This shows we lack a platform to build such giants and foster innovations on a scale seen in other regions. 

Europe suffers from a fragmented market and lacks the kind of aggressive venture capitalism seen in China and the US, despite having the necessary capital. Our market is scattered, which makes it difficult to harness resources and invest on a scale that can compete with these countries. This structural issue limits our ability to foster large-scale technological innovations. 

Q: Do we have a culture that boosts innovation in Europe, similar to what is seen in the US? 

Hanna: It's not a coincidence that tech giants like Microsoft, Amazon, Apple, and IBM are all based in the US. They thrive there because of a culture that aggressively supports innovation. In Europe, and particularly in Finland, while we are an engineering-strong country, we lack the venture capital ecosystem that fuels such massive growth. Our innovative capacity is there, but not on the same scale. 

Q: Can you expand on how Finland's historical and economic context affects its innovation? 

Hanna: Certainly. Finland has long been technologically advanced, yet historically, we've never had the wealth to support the kind of lavish investments in tech that you see in the US. Our financial prudence and smaller scale have restricted our ability to compete as a home for global tech giants. Even if Finnish companies possess the technological know-how, scaling up remains a challenge. Unlike in the US, where tech companies have grown and dominated globally for decades, we in Europe need to develop mechanisms that allow for similar scaling and impact. 

Q: How should Europe adjust its focus to enhance its technological stature globally? 

Hanna: Europe's focus on stringent regulations, while important for privacy and security, might also be limiting our competitive edge. We should instead concentrate on fostering a more unified internal market that could compete on the global stage. We need to balance regulation with support for innovation to avoid falling behind other regions like the US, China, and even emerging tech hubs in Africa and India. 

Q: What future plans does Siili have for advancing its use of AI? 

Hanna: Looking forward, we plan to expand our AI training programs, further empowering our teams to leverage AI in more innovative ways. This continuous learning environment not only benefits our internal processes but also enriches the solutions we offer to our clients. We aim to lead by example, showcasing how integrating AI can transform business operations not just technically, but also culturally within organizations. 

Q: Wrapping up the interview, can you tell what AI tools you use? 

Hanna: I use ChatGPT quite extensively, especially for tasks like copywriting and language checking. It's invaluable for drafting communications and formulating responses to complex customer situations. However, I’m also mindful of its limitations—it's not suitable for tasks that require deep market analysis or high-level personalization. 

ChatGPT can save a lot of time, but sometimes the outputs feel a bit too generic. So, there's a balance to be struck in using AI tools like ChatGPT. It's about using these tools wisely. For straightforward tasks or initial drafts, AI can be a huge time-saver. But for anything that requires depth, nuance, or detailed analysis, it’s important to either heavily modify the outputs or not use AI at all. This ensures the content remains authentic and genuinely useful. 

I always ensure that the final output is refined by human intelligence. For instance, I might use AI to draft an email or a report but then revise it extensively to add a personal touch or detailed analysis. It’s also a useful checkpoint tool—helping to ensure all relevant themes or topics are covered before finalizing a piece. 

Q: And what about using AI for presentations or critical communications? 

Hanna: For presentations, especially in tools like PowerPoint, AI doesn’t really capture the essence of what needs to be conveyed. These tools require a deep understanding of the content and the audience, something AI can't fully grasp yet. Therefore, while AI helps with the groundwork, the critical aspects of tailoring the message and engaging the audience should always be handled personally. 

Hanna Hagstrom is the Business Unit Director, Industry at Siili Solutions