Around the same time, the Financial Times published a piece noting that while investors are betting on AI-fueled chaos and disruption, history tells a different story. Past technological revolutions—from the PC to the internet and cloud—rarely wiped out incumbents. Savvy established players adapted, integrated the new capabilities, and often emerged stronger.

Reading these together crystallized something I’ve been observing in our work at Datarella and across the broader tech landscape: the most probable path for AI in business is neither a dystopian job apocalypse nor a chaotic upending of entire industries. It’s a pragmatic, evolutionary integration — one that rewards organizations willing to embrace AI’s inherent “weirdness” while building solid foundations to prevent disorder.

As someone who has spent decades building companies and helping enterprises navigate digital transformation, I believe this balanced view is crucial. AI won’t replace everything overnight, but it will reshape how we work — if we let it.

Why AI So Often “Dies” in Traditional IT Settings

Mollick’s diagnosis rings especially true because we see this pattern repeatedly in enterprise environments. AI isn’t deterministic software with predictable, repeatable outputs. It’s generative, highly context-dependent, and frequently surprising. When handed over to IT teams whose primary mandates are security, compliance, uptime, and cost control, the instinctive reaction is understandable but often counterproductive:

• Wrapping every experiment in lengthy approval processes
• Demanding detailed ROI projections before any meaningful pilot
• Forcing AI into legacy tech stacks without rethinking underlying workflows
• Prioritizing only the safest, most obvious use cases

The outcome? Countless pilots that never scale. Recent analyses, including Deloitte’s 2026 State of AI in the Enterprise, show that while employee access to AI tools has exploded, the move from experimentation to full production remains limited. Issues like poor data quality, skills gaps, and overly cautious governance continue to create friction.

Harvard Business Review has noted a similar phenomenon: widespread AI usage paired with disappointing returns, with adoption often stalling at the integration stage. The core mistake isn’t poor execution—it’s treating AI like just another CRM or ERP module rather than a fundamentally new way of thinking and working.

History Offers Reason for Optimism

The Financial Times article provides a reassuring counterpoint. Technology revolutions rarely play out as pure creative destruction. Incumbents who invest in complementary capabilities—new skills, redesigned processes, and updated organizational structures—tend to adapt and thrive.

In 2026, I expect the real winners won’t be only the flashy AI-native startups. They will be established companies that intelligently combine their deep domain expertise and proprietary data with AI’s capabilities. Those who redesign workflows for genuine human-AI collaboration (sometimes called “co-intelligence”) and scale thoughtfully from pilots to enterprise-grade agentic systems will gain the edge.

Reports from PwC and others speak of a “disciplined march to value”: clear strategies, measurable outcomes, and governance frameworks that protect without suffocating innovation.

What the Most Likely Future of AI in Business Looks Like

Looking ahead to late 2026 and 2027, here’s the trajectory I consider most probable:

1. Scaling from pilots to production — More organizations will move a significantly higher share of AI projects into live use, particularly through agentic AI systems that handle multi-step workflows autonomously.
2. The J‑curve of productivity — Expect initial periods of flat or even negative returns as companies rewire processes and roles. Once the complementary changes (new data pipelines, decision protocols, and team structures) are in place, gains should accelerate sharply.
3. Governance maturing — Robust frameworks for responsible agentic AI, data quality, and risk management will become standard. “Shadow AI” will gradually decline as secure, enterprise-ready platforms improve.
4. Incumbents leveraging their data moats — Organizations with clean, well-governed data and strong domain knowledge — especially in regulated or complex industries—will often outperform pure AI disruptors.

This isn’t a utopian revolution or a total failure. It’s an evolutionary transformation, provided we avoid the trap of over-standardizing AI too early.

Five Practical Principles for Embracing AI’s Weirdness

Drawing from Mollick’s insights, historical patterns, and the latest enterprise reports, here are the principles I believe forward-thinking leaders should adopt:

1. Deliberately embrace the weirdness — Create space for teams to experiment and discover unexpected applications. Encourage “labs” or crowdsourced exploration. Treat AI as a creative collaborator rather than a simple automation engine.
2. Invest in rock-solid data foundations — Data quality and governance remain the biggest barriers. Without trustworthy, well-integrated data, even the most advanced models produce unreliable results. This is an area where specialized expertise in unifying silos and building real-time, compliant pipelines makes a decisive difference.
3. Redesign workflows for human-AI co-intelligence — The goal isn’t to automate jobs out of existence but to augment human strengths. Let people focus on judgment, creativity, and relationships while AI handles analysis, drafting, and routine tasks.
4. Deploy governed, secure agentic systems — Autonomous agents represent the next frontier, but they require thoughtful orchestration, threat modeling, and compliance built in from the start.
5. Measure what truly matters and iterate patiently — Look beyond vanity metrics. Track real business impact—revenue, cost efficiency, customer outcomes—and accept that returns often follow a J‑curve.

Reflections from the Trenches

At Datarella, we’ve been helping organizations move past the hype and pilot purgatory for years. Our focus on secure AI agent development, full-stack modernization, privacy-preserving architectures, and (where appropriate) decentralized approaches is designed precisely for this moment: enabling companies to harness AI’s strange power without inviting chaos.

Whether it’s building production-ready autonomous agents, creating reliable data platforms, or integrating AI into complex legacy environments, the key is combining technical depth with practical business judgment.

The future of AI in business isn’t about tearing down your existing structures or gambling on total disruption. It’s about evolving how your organization learns, decides, and creates value—by thoughtfully embracing AI as the odd, powerful tool it is, while strengthening the data, governance, and cultural foundations it requires.

If you’re ready to move from interesting pilots to scalable impact—without letting AI “die in IT”—I’d be happy to explore how we can support your journey.

Let’s connect.

The post The Most Likely Future of AI: Embracing Its Weirdness Without Descending Into Chaos appeared first on MICHAEL REUTER.

Since the token qualifies as investment token (“Vermögensanlage” in german), it is not tradeable on cryptocurrency exchanges. Token holders receive a fixed interest of 3% and may sell the token back at nominal value.

Why Tokenization?

Traditionally, real estate has been financed by owners, banks, or external investors participating in real estate funds. The investment process in real estate is complex, takes time and effort. By using blockchain technology and cryptocurrencies or tokens, this process can be simplified and made much more efficient.

Liquidity

First, there is the securitization aspect of tokenization:: by making an illiquid real estate asset completely liquid, this type of investment is made accessible for a much larger target group of potential investors. Traditionally, mainly wealthy individuals or companies could invest in real estate. With a liquid asset, such as the Connex Coin, an individual can become a real estate investor starting with a 10 EUR investment.

Besides having a bank account in an EU country and a registration, nothing else is required to buy this investment token. Since Connex Coin is a non-tradable, stable investment token, the token holder receives a 3% interest paid directly to her bank account. Information about the personal holdings is displayed in the personal account. By using tokens, securitization is made easy and efficient.

Programmability

Tokenization is much more than securitization: a token can be described as programmable money. In other words: tokenization adds programmability to an asset. This way, business logic can be introduced, reducing the need for manual settlements and smart contracts can have functions for automatic transactions, formulas for calculating asset prices, and other specific features at marginal costs. So, what kind of business logic can you add? Simple answer: any. And exactly this large number of degrees of freedom makes it somewhat challenging to start with.

At RAAY RE, we have started by leveraging our proprietary (Crypto) Smart Wallet by adding features that allow token holders making use of specific property-related functions, such as granting access or allowing for the use and payment of facilities. We will elaborate more on this aspect of programmability in the next post. From our perspective, the programmability of formerly static assets provides great opportunities for the real estate industry.

Immutability

A digital, integer trail of transactions proves a history of ownership and eliminates data misuse and fraud, such as double-spending. Furthermore, the consistent historical record of all transactions allows for realtime, frictionless reporting. Just ask your asset managers and CFOs about their administrative headaches that traditionally could only be healed by tremendous accounting efforts. With a guaranteed complete historic data set of all transactions, this headache can be eliminated completely. Tokenization helps to minimize administrative efforts, timewise, and with regards to costs.

Tokenization And Asset Tradeability For A Digitized Real Estate Industry

For RAAY RE, the tokenization of a share of the Connex building is the first proof of functionality in our tokenization module, which is one part of our Digital Operating System for the real estate industry. There will be more assets tokenized – as well as in terms of securitization, and, specifically regarding the programmability aspect of tokenization: our tokens will come with built-in business logic that will unleash the full value of real estate assets.

The post Tokenization And Asset Tradeability For A Digitized Real Estate Industry appeared first on MICHAEL REUTER.

The real estate industry has been booming for more than 10 years and most players within the industry have great balance sheets combined with huge profits. Every boom phase comes to its end, eventually. When early market indicators start to change, forward-looking market participants adapt their strategies and prepare for slowing markets. Blockchain is a foundational technology that’s best suited not only for simplifying businesses, streamlining processes and eliminating inefficiencies, which is most needed in times of softening markets but at the same time, blockchain is a great enabler of new business models that had not been possible to offer before.

We have big plans with RRE, aiming at leveraging blockchain technology to disrupt the real estate industry. We will start with tokenizing illiquid real estate assets.

Leveraging Blockchain Technology To Disrupt The Real Estate Industry

Since we at Datarella and RAAY are no experts in real estate, we are happy to have teamed up with Hammer AG and Wertgrund AG, two premier real estate companies with great track records. For me personally, it’s a real honor that Hans Hammer, CEO of Hammer AG, and Thomas Meyer, CEO of Wertgrund AG, are willing to start this fascinating journey together with us. Both of them not only represent highly successful companies, but they are very entrepreneurial types who think outside the box and have this superb mix of being curious and explorative, as well as reputable and down-to-earth at the same time. It’s an absolute pleasure to work with them.

I’m looking forward to co-building RAAY RE with Datarella, RAAY, Hammer, and Wertgrund — a team that is best suited for making the real estate industry more efficient. If you‘re interested in discussing our plans let‘s meet at ExpoReal in October!

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