2025 Tech Trends, Insights & Recommendations
For the past 10 years Magnus Jern has shared his thoughts in terms of technology trends and insights for success in leveraging these trends. The purpose is to provide hands-on tips for every organisation to succeed.
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This time it’s more challenging than ever due to the rapid development of AI tools and platforms. However, our belief is that the key to success is a combination of AI technology, Human Centric Design, Security and a Data-driven outcome based approach. Below we will dive deeper into this.
Here are the key trends that we think will make your organisation successful when it comes to leverage technology in 2025 and beyond.
1. KISS (Keep it Simple, Stupid)
When developing new enterprise and consumer apps always start with solving the simplest core use case first to test and then expand. We constantly see both marketing and IT organisations overcomplicate things. The larger the organisation, the bigger the scope. Design by committee, overly cautious legal and finance teams and processes lead to constant scope creeps.
Why:
Large complex scopes lead to long leadtimes, high costs and often the projects are bound to fail even if it was a great idea.
Simplifying a project can lead to faster development, reduced costs, and increased user satisfaction.
Recommendation:
Create a bare minimum scope for version 1 the MVP which may not pass the requirements for launch but that can be used for testing
Keep it Stupid Simple. Simplify, simplify and simplify.
Use tools like Gemini, ChatGPT and Copilot to simplify the criticize and simplify the scope
Example:
When La Caixa bank in Spain launched peer to peer payments (Bizum) in Spain they launched it as a separate app that only did one thing. Input a phone number or contact and enter the amount to send and approve the transaction. Later they integrated into their bank app which took one year.
2. No bots here – Human touch still matters
Most organizations see customer support as a cost center and therefore it’s often the first to be replaced with AI bots. But what about the user experience? In most cases the customer experience is severely degraded with a bot due to a combination of poor implementation, lack of user testing and too much emphasis on the bot rather than the customer solution.
Therefore your cost saving may actually cost more than it saved. In the long run.
Why:
Despite recent advances in AI many out of the box customer support and sales chatbots still suck. If you’re a bank, government agency or utility company where customers have no choice then you can get away with it but most organizations don’t. Have you noticed that Apple, Google and Amazon that are technology leaders, rarely use the term chatbot?
Whenever I see the word chatbot on a contact or support page it makes me worried that I’m going to end up in an endless loop. Use technology to solve my problems but don’t tell me to speak to a bot.
Recommendation:
To begin with Use AI assistants to augment human agents and offer live chat support during peak hours or outside of working hours
As the AI assistant improves over time start migrating customers to the automated service while letting the human agents focus on problems that require human interaction
Human Touch: Ensure there are always easy options for users to connect with real humans, especially for complex issues.
Example:
KLM Bluebot. This AI assistant can book flights, check flight statuses, and provide personalized travel recommendations through Facebook Messenger and WhatsApp. The seamless integration with KLM’s customer support system allows for a smooth handover to a human agent when needed. The only thing we don’t like is the name.
3. Apps Still Rule
It’s now been almost 20 years since we started working with mobile apps. During the early days of Palm pilots, Symbian and Java the role of mobile apps was not obvious. And a few years after the Apple and Android appstores were launched we were told over and over again that apps were dead to be replaced by web. But here we are more than a decade later and apps play a more important role than ever in solving user problems, enhancing user experience and delivering customer value.
Why:
Mobile apps offer unparalleled user experience, personalization, and offline functionality.
They are essential for capturing customer attention, building brand loyalty, improving employee productivity and driving business growth.
With AI and voice control finally working we will see a new big leap in this space
Recommendation:
Prioritize mobile app development as a core part of your IT and digital strategy.
Cross-Platform Compatibility: Ensure the app works seamlessly across different devices and platforms.
Invest in app design, development, user testing and continuous improvements to deliver exceptional user experiences.
With AI tools and auto QA you can deliver 10x as many apps as before with better quality using the same resources as before
Example:
Expense management app for employees that integrates directly with the accounting system by just taking a photo, extracting the information from the receipts, workflow approval, etc.
4. AI or DIE – Your 2025 Wake-Up Call
The art of the possible has completely changed. We believe that AI tools will double productivity in enterprise IT and marketing technology in the coming years. For most people AI is now synonymous with LLMs like ChatGPT, Copilot, Claude and Gemini. 99% of the use cases are answering questions and creating content. This means that these tools are often the starting point when organizations explore how to leverage AI. This is exciting but it’s not where you will find the biggest gains.
Why:
AI is so much more than chatbot LLMs. There are already 1000s of general and specialized AI tools including agents that can help businesses solve everyday problems.
Companies that don’t leverage AI to achieve productivity gains in the coming years may go out of business.
Implications: Bigger is better as they have more resources and scale to automate with AI.
Recommendations:
Train and experiment using AI tools with all your employees keeping an open mind.
To harness AI’s potential, start by breaking down what your organisation does into tasks (e.g. data entry, report generation, reading reports, copy checking, translation or common customer issues). Identify which can be automated, enhanced, or transformed by AI or other advanced tech.
Go through the wish-list of things your employees would like to improve your business whether it’s website, expense reporting, invoicing or something else. Prioritise the most important and evaluate if the can be achieved with the help of (2).
Then find the right tools and methods to solve your problem. Experiment.
Examples:
One of our eCommerce clients automated the process of competitor price (and promotion) checking online including summarising, analysing and making recommendations. This meant that they could react much faster and avoid sale drops when competitors did unexpected campaigns.
The AI design tool Semanttic allows you to create a prototype of an enterprise or consumer app in less than 15 min to test a concept. For large companies this means that they can test new apps almost as easy as writing a note on a post-it.
And if this is not enough here are 200 examples of Microsoft Copilot in action.
5. AI doesn’t replace coding – yet
App and website MVPs can be delivered using AI tools without coding but not ready for full scale production yet. Nor can you be sure that the code actually works in the environment you employ it. Plan to use a combination of AI coding tools and developers if you are developing a solution that will be used beyond concept testing.
Why:
We’ve tested many of the tools ourselves to create apps, websites, code for specific apps within websites and much more. Sometimes they work great straight away to solve simple problems but other times it’s completely misunderstood.
While AI tools can generate code, they’re not yet reliable for complex, full-scale production applications. There are often compatibility and performance issues.
Recommendation:
Use AI to generate initial code but rely on human expertise for optimization and debugging.
Start by using AI coding for smaller problems and to generate prototypes. Once you have a working prototype, work with a human coder to redesign the application (leveraging AI tools for efficiency).
If you are not a coder, experiment with creating code yourself to solve business problem and challenge your technology colleagues internally or externally
Example:
With Replit, Loveable and other prototyping tools we leverage the AI generated prototype code to test the concept with users. Once we have tweaked and signed off on the MVP scope we use experienced developers to develop it while using AI coding tools to speed up development.
6. Leverage Auto QA in Combination with Human User Feedback
Automating quality assurance (QA) processes with AI is a game-changer. By combining automated testing with human feedback, businesses can significantly improve software quality and reduce time-to-market.
Why:
Faster Time-to-Market: Automated tests can be executed quickly and frequently, identifying and fixing bugs early in the development cycle.
Improved Quality: AI-powered testing tools can detect subtle defects that might be missed by manual testing.
Enhanced User Experience: Human feedback is critical in terms of ensuring that the software meets user expectations and delivers a seamless experience.
Recommendation:
Implement AI-Powered Testing Tools: Utilize tools that can generate test cases, execute tests, and analyze results automatically.
Prioritize Test Automation: Focus on automating critical test cases to maximize the benefits of automation.
Leverage Human Feedback: Gather feedback from beta testers, customer support, and user analytics to identify potential issues and areas for improvement.
Examples:
Test.ai and Applitools enble us to automate the testing process of new apps running through 100s of user scenarios, browser and mobile phone variants with limited human work required. This means we can cut down on leadtime, resource requirements and improve quality.
7. Master the Balance Between In-House and Outsourced Talent?
Successful organizations are increasingly outsourcing specialized IT functions, such as app development and artificial intelligence, to experts who possess deep domain knowledge. Furthermore rather than offshoring or nearshoring they find the location that makes the most sense for each project.
Why:
Outsourcing and freelancers have a comeback as companies can leverage specalised expertise in every area, lower cost resources and manage peak demand better.
Recommendations:
Outsource specialized IT functions to experts in the most suitable locations to leverage domain knowledge, cost-effective resources, and effective demand management.
Critical Success Factors: Clearly communicate goals that can be measured throughout the project to ensure everyone is on the right track. This can also align eveeyone with KISS (point 1).
Example:
One of our clients with an IT team of 1000+ people was facing a huge backlog of apps to be delivered to support a new productivity initiative. Although the competency existed internally the team had not had the chance to keep up with AI toolchains such as Cursor, Magic and Augment. xHuman Labs was challenged to take on 10 of the apps and delivered UX prototypes of all of them within 4 days. The integration and development was completed for all 10 apps in 12 weeks.
8. Cybersecurity is invisible—until it’s not.
In the past year I’ve seen several companies almost go bankrupt due to security breaches. But prioritizing security often feels like an uphill battle as the results aren’t immediately visible.
Why:
Cyberattacks can lead to significant financial losses, reputational damage, and legal consequences.
As the dependency on software and automation increases, so do the risks associated with cyber threats.
Ensuring robust cybersecurity measures is essential to protect sensitive data and maintain customer trust.
Recommendation:
Proactive Measures: Implement proactive cybersecurity measures, such as management risk reviews, regular security audits, penetration testing, and vulnerability assessments.
Employee Training: Conduct ongoing cybersecurity training for employees to ensure they are aware of the latest threats and best practices.
Customer Security: Help your customers use high quality passwords and authentication by making it easy for them
Multi-Factor Authentication: Use multi-factor authentication to add an extra layer of security to sensitive systems and data.
Example:
One of our clients (a well known brand) suffered a phishing attack that exposed customer payment data with the hacker blackmailing them for a large amount to not expose the data. The issue was settled at a large cost for the business.
To prevent future breaches, they implemented a multi-layered cybersecurity strategy including requiring multi-factor authentication for all customer and employee accounts. They also deployed Darktrace (AI-driven tool) to monitor for unusual network activity and detect potential breaches in real time. Finally they conducted mandatory annual cybersecurity training for all employees, using realistic phishing simulations to improve awareness and hired a cybersecurity freelancer to perform regular penetration testing and vulnerability assessments.
9. Foster a Data-Driven Outcome based Culture
Cultivating a culture where data is integral to decision-making processes can drive innovation, efficiency and business growth. But the key is to focus on Outcome. Most initiatives and change should have a measurable target no matter how small and be measured afterwards to see if they lead to the desired outcome..
This does not mean that everything needs to be data-driven. Areas like culture, creative and brand might not be easily measured.
Why:
A data-driven culture ensures that decisions are based on empirical evidence rather than intuition or guesswork. This approach leads to more accurate, efficient, and innovative business strategies.
Recommendation:
Leadership Buy-In: Ensure leadership supports and champions the use of data in decision-making and makes it part of OKRs and other individual targets.
Data Literacy Programs: Invest in training programs to improve data literacy across the organization including how to set target and measure results.
Accessible Data: Make data easily accessible to employees at all levels to encourage data-driven insights and decisions.
Example:
At Tappwater, we established a simple yet powerful rule: any initiative requiring over 4 hours of effort must have measurable success factors. Each initiative’s success is evaluated monthly against these goals, with outcomes rated and discussed. Twice a year, we review employee track records based on these data-driven results, identifying opportunities for growth and improvement.
This approach has transformed Tappwater into a learning organization, where data insights drive smarter decision-making, improve project impact, and foster a culture of continuous improvement. Over time, it has significantly increased the success rate of initiatives and strengthened accountability across teams.
10. Prioritize User Experience (UX)
No trends and tips presentation would be complete without emphasis on the importance of user experience and human centric design.
Why:
A great user experience is crucial for attracting and retaining customers. User-centric design can lead to higher user satisfaction, increased engagement, and improved brand loyalty.
Recommendation:
Usability Testing: Regularly test designs with real users to identify usability issues starting with the first prototype of a new product or service.
Iterative Design: Use iterative design processes to continuously refine and improve the user experience.
User Touchpoint Reviews: Review the end-to-end user journey at least once per year to identify issues and areas of improvement.
By implementing these suggestions, organizations can further enhance their success in leveraging technology for productivity, cost savings and most importantly success.
Example:
A SaaS company we worked with noticed that customer churn was increasing despite offering a competitive product. To address this we conducted usability tests with real users, uncovering frustration with complex navigation and inconsistent interface design. Next we adopted an iterative design approach, rolling out monthly updates based on feedback from users. Finally we performed a review of the end-to-end user journey, identifying gaps in onboarding, which led to the creation of a step-by-step interactive tutorial for new users.
The improved UX resulted in a 25% reduction in churn within six months and a significant boost in referrals.
Final words
We hope that these hands on tips and insights will help you define your technology strategy and priorities for the coming years. Feel free to reach out to us to discuss any or all of the trends. We are here to help!
Magnus and the xHuman Labs team
