Networks and Technology
A treasure trove of digital innovations
The boundaries between civilian and military technology are blurring. In the right hands, these technologies help make our world a safer place. Meanwhile, artificial intelligence is being developed to operate more autonomously and to interpret its surroundings and interactions in increasingly human ways. Instead of hype and hyperbole, the coming year looks to be more about practical innovations and insightful applications of technology.
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Machine customers are developing better trade skills
What if an AI system overseeing a company’s facilities or warehouse logistics could hop onto an online store to make purchases when it detects shortages or avenues for improvement? With the mass adoption of IoT devices, experts suggest that machine customers will become the most significant agent of transformation in the commercial sector this decade.
By estimates, AI clients will be highly trained as quality and price-conscious consumers by 2026. Companies are encouraged to examine their internal infrastructure to ensure the smooth implementation of new automated services. Staff training will also be essential to ensure employees can utilise automation-based programs and systems seamlessly in the future.
As AI assistants continue to evolve, it’s likely that the capabilities of AI customers tailored for business use will exceed expectations in the future. However, the defining factor in this equation will be the company’s infrastructure: the more we assign autonomous responsibility to AI, the more comprehensive our understanding of AI’s underlying deep-level structures must be.
By estimates, AI clients will be highly trained as quality and price-conscious consumers by 2026.
GovTech is transforming digitalisation in the public sector
GovTech refers to technologies like the digital identity wallet set to be released in Finland in 2026. GovTech is projected to claim a substantial share of the software market in the coming years: estimates suggest that the market value of GovTech will exceed one trillion euros by 2028.
The projected success of GovTech is based on the practicality-minded and human-centered approach of government-funded software development. While it is common in the digital sector that new technologies enjoy a brief ride on the hype curve until they’re pulled into swift descent and culled of their unusable features, GovTech solutions are designed with the needs of the population in mind. This approach is the best way to ensure that new digital solutions are meaningful in everyday use, while also making them relatively easy to integrate into daily operations.
For GovTech to thrive, it requires an open environment, and experts believe that the development of governmental technology needs more commercial and entrepreneurial insight. It is highly likely that we will see a substantial increase in partnerships and collaborations between digital industry companies and the public sector in the coming years.
Sources:
Finnish Government
World Economic Forum
GovTech solutions are designed with the needs of the population in mind.
Dual-use technology development accelerated by NATO initiative
Dual-use technology refers to technology that can serve both civilian and military purposes. Examples of dual-use technology include GPS navigation, thermal and night vision cameras, and drones.
NATO’s newly established DIANA initiative aims to accelerate the development of dual-use technologies on a global scale by providing member countries' businesses with resources, networks, and collaboration opportunities. The goal is to develop deep-tech solutions that have applications both in civilian markets and in national defence and threat mitigation, enabled by breakthroughs in fields like artificial intelligence, quantum computing, and robotics.
According to VTT Technical Research Centre of Finland, while defence-focused solutions have traditionally relied on a limited number of expensive units, applications originally designed for civilian use also enable the deployment of smaller, more cost-effective devices and software. Characteristics of the commercial technology market, including the speed of innovation and the transition from design to prototype, are also expected to cut down development time by years.
Sources:
Defence Innovation Accelerator for the North Atlantic (DIANA)
VTT (in Finnish)
The goal is to develop deep-tech solutions that have applications both in civilian markets and in national defence and threat mitigation.
AI inspires social and healthcare innovators: “If not in Finland, then where?”
Imagine AI donning a white coat, equipped with a stethoscope – it’s not just science fiction anymore. In Finland, AI is taking bold steps into the healthcare sector, offering the potential to revolutionise how social and healthcare professionals work. And Finland is at the forefront of this transformation, actively seeking innovative ways AI can enhance the lives of both professionals and patients.
Jarmo Pulkkinen from DigiFinland is leading the charge, coordinating the AI ecosystem initiated by the Ministry of Social Affairs and Health. The network brings together actors from the public, private, and third sectors, and the ministry is funding AI trials in the wellbeing services counties with up to three million euros. From his front-row position, Pulkkinen senses the growing excitement around AI spreading throughout the wellbeing services counties.
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“With over 150 different organisations involved – from municipalities and companies to educational institutions – we’re quickly building a collaborative network. Our goal is to bring healthcare professionals and AI developers together to create real-world solutions that make a tangible difference,” Pulkkinen explains.
For the Finnish government, AI isn’t just a buzzword. It’s seen as a crucial part of the broader digital transformation aimed at solving the mounting challenges in healthcare. Before launching the AI ecosystem, an extensive study identified key areas where AI could make the biggest impact in the sector.
Real solutions, not just hype
Healthcare professionals, especially doctors and nurses, are seeking genuine improvements to their work, not more tech buzz. AI offers a way to reduce administrative burdens, freeing up more time for patient care. From diagnosing illnesses to predicting service needs, AI is already playing a supportive role in various healthcare tasks.
We’re after entirely new ways to leverage AI.
“For instance, AI that recognises speech and records diagnoses during a doctor’s appointment is almost ready for widespread use,” Pulkkinen says. “But we’re not just looking for more of the same, we’re after entirely new ways to leverage AI.”
However, not all digital solutions in Finland’s healthcare system have been warmly received. Clunky patient information systems and overly complex software have left many healthcare professionals frustrated. Pulkkinen, who has been involved in healthcare digitalization since the early 2000s, recalls being astonished when he saw the potential of AI firsthand.
“People need to experience the real value of AI. Everyone deserves that ‘wow’ moment – whether it’s realising AI can save time in home care or improve decision-making. Small innovations that ease daily tasks are just as valuable as large-scale national projects,” Pulkkinen says.
Overcoming barriers to AI adoption
Despite the excitement, challenges lie ahead. One major hurdle is the flow of information within the highly fragmented healthcare sector, where organisational silos and strict regulations often slow progress. Breaking down these barriers will require a nationwide health information repository and better co-operation between the state and regional authorities.
The safe and ethical use of AI is another key concern, particularly regarding patient privacy and data security. Pulkkinen acknowledges that while legal safeguards are essential, overly rigid interpretations could hinder innovation.
“For AI to truly help a doctor make better decisions, it needs access to patient information. Right now, something as simple as a missing consent form can block this access. This is why data security, privacy, and legislation play such an important role in this initiative,” he adds.
Can Finland lead the AI healthcare revolution?
While AI’s primary goal is to address Finland’s healthcare bottlenecks, the country is well-positioned to develop competitive solutions for global markets. With healthcare spending accounting for nearly 20% of the GDP in the U.S., for example, the demand for AI-driven solutions is skyrocketing.
Pulkkinen believes that Finland, with its advanced healthcare infrastructure and collaborative culture, has the perfect conditions to lead this revolution.
“If we can’t do this in Finland, then where? We’ve got the right attitude, cutting-edge technology, and a strong spirit of co-operation. We’re seeing experts collaborate across sectors with ease,” he says.
AI is set to become a key player in healthcare, and as new applications emerge, its impact will be felt in the years to come. Improved accessibility, higher quality care, and more efficient services are all on the horizon.
With enough creative digital tension, we can truly harness the potential of AI in healthcare.
Pulkkinen is confident that, despite the challenges, the collaboration between government authorities, companies, educational institutions, and wellbeing services counties will pave the way for AI’s success in Finland:
“We’ve got a glass-half-full mentality, and that’s what inspires me. With enough creative digital tension, we can truly harness the potential of AI in healthcare – both in the short term and for generations to come.”
Humanoid robot development is ramping up – but robots won’t be replacing experts
The market for humanoid robots is expected to grow enormously over the next decade. The primary development drivers are the advancements in generative AI and decreasing production costs. By 2035, the market value of humanoid robots is projected to grow sixfold, reaching approximately 40 billion.
Humanoid robots can be utilised in industries such as manufacturing, healthcare, and of course households. They can serve in both monitoring and operational roles. Humanoid robots are guided by adaptive, learning-based AI and are also capable of physically demanding tasks, as they do not experience fatigue like their human counterparts.
The use of AI assistants and robotics in healthcare is set to expand significantly in the coming years. Professionals in the field praise AI’s ability to enhance diagnostics, treatment planning, medical research, and patient monitoring. However, experts also caution that AI can sometimes rely on flawed or biased data, which leads to inaccurate conclusions, diagnoses, and treatment recommendations. The development of AI and robotic assistants will always require careful oversight and human supervision.
Sources:
Harvard School of Public Health
Freethink
Humanoid robots are guided by adaptive, learning-based AI and are also capable of physically demanding tasks.
Empathetic AI makes people feel heard and understood
Empathetic AI is a general term for AI systems designed with emotional intelligence embedded as a core tenet. According to industry leaders, leveraging emotionally intelligent AI will soon become crucial for businesses looking to optimise customer interactions and improve internal processes.
At its core, empathetic AI aims to discern the needs of its human conversation partner, which are often embedded in subtle cues and contextual nuances. In other words, emotionally intelligent AIs are trained to act, interpret, and respond empathetically before offering solutions or next steps to human beings.
Empathetic AI models are also being trained to operate with greater transparency and openness. Instead of providing incorrect or misleading information, emotionally intelligent AIs are able to indicate when they lack sufficient information to respond. Acknowledging errors and limitations is a key component of human interaction. Industry experts have noted that one of the most important qualities of empathetic AIs is their ability to admit when they don't have all the answers – a skill that remains surprisingly challenging for many of today's AI systems.
Sources:
Forbes
Emotionally intelligent AIs are trained to act, interpret, and respond empathetically before offering solutions and next steps to human beings.
DNA set to revolutionise data storage capacity
The amount of digital data continues to grow exponentially, which puts strain on traditional storage solutions. DNA, also known as the blueprint of life, is an exceptionally efficient medium for data storage: one gram of DNA can store around 215 petabytes of data. A single cup of DNA could theoretically store all recorded information.
Other advantages include the stability and longevity of DNA as a storage medium and significantly lower energy consumption compared to traditional digital solutions. Current drawbacks are the high cost of DNA synthesis and relatively slow writing speeds. Currently, writing around 100 bits of data to DNA takes two hours and costs about a dollar, so practical application remains limited for now.
These technological barriers are likely to break down eventually. Experts in the field believe that DNA storage technology will develop in giant leaps once the challenges of costs and transfer speeds are overcome. Using DNA as a storage medium may still feel like a distant dream, but then again, a modern smartphone is more advanced than a 1960s moon rocket. Development tends to catch up with us faster than we expect.
Sources:
IEEE Spectrum
Trends in Biotechnology
Using DNA as a storage medium may still feel like a distant dream, but then again, a modern smartphone is more advanced than a 1960s moon rocket.
Experimentation is key to the AI revolution – business leaders must take action now
AI is part of our everyday lives, but its true potential lies in the future. For companies to effectively use AI, they need a culture of experimentation and continuous learning. At best, leaders will see their organisations thrive on new business opportunities and more efficient working methods. At worst, things will continue as they have always been, and progress will slip away.
Already, AI is helping, for example, to summarise vast amounts of data into easily digestible form and translate texts or speech from one language to another in the blink of an eye. It can transcribe speech, refine text, generate images and videos, and assist customer service agents in real time.
For example, AI can answer personal phone calls for us and find out what's up, so we know whether we should jump in personally – or let the AI handle it on its own.
“There's still a bit of hype around the AI talk, but the revolution will be big. We certainly don't yet know the extent of the change coming,” says Anna-Mari Ylihurula, SVP, Corporate Business at DNA.
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Real benefits will be uncovered through experimentation
The best way to discover AI’s potential is to experiment. Executive boards must actively encourage the adoption of new tools and ensure that their opportunities and threats are understood. While AI raises ethical, financial and regulatory issues, it also offers business opportunities and efficiency gains.
Even a failed experiment is a valuable result and a learning experience for the future.
“Every business leader should be interested in learning how AI is already used in different industries and companies. Different use cases can provide surprising inspiration for your work,” Ylihurula encourages.
Rapid experimentation minimises risk, accelerates learning, fosters innovation, and supports cultural change. The fastest developing companies are those that first test new, interesting AI solutions on a small scale, analyse the results, and then decide whether to develop them further or abandon them.
“Experimentation is affordable, so it pays off. In AI experimentation, it is important to learn from each step and iteratively improve the outcome. It's good to remember that even a failed experiment is a valuable result and a learning experience for the future. It's not just the management's job to dictate the use of AI tools; the whole organisation needs to remain curious, active, and self-directed,” Ylihurula adds.
Sharing learnings contributes to collective development
Of course, experimentation alone is not enough. Sharing the lessons learned from experimentation is key to organisational development. A culture of knowledge sharing requires active participation from managers. Leaders can lead by example by sharing their learning experiences, whether successful or unsuccessful.
Our staff use the same solutions we offer our customers.
“Technological innovations not only affect business but also the organisation's culture. Today, everyone from trainees to managers must be willing to learn and share their learnings,” says Ylihurula.
As AI tools began entering businesses’ everyday lives, DNA was at the forefront of experimenting with how best to use them in its own work. DNA's staff have long used its own support intelligence developed specifically for DNA and Copilot tools as their own internal support intelligence. AI is also widely used in customer service, sales, and marketing.
“It is important that our staff use the same solutions we offer our customers. Through our learnings, it is natural for us to share with customers how we have benefited from the solutions and to share use cases and deployment experiences. Of course, we also actively share information across the Telenor Group,” says Ylihurula.