As we stand at the precipice of the most significant technological transformation in human history, the question isn’t whether Artificial General Intelligence (AGI) will arrive—it’s how quickly we can adapt our business models to thrive in this new paradigm.

At DigiEx Group, we’ve spent years building AI-driven software solutions and talent ecosystems across global Startups, and we’ve witnessed firsthand how rapidly the landscape is changing. The convergence of accelerating AI capabilities and shrinking AGI timelines demands that software development companies fundamentally reimagine their value proposition.

The AGI timeline: Closer than we think

The latest predictions from industry leaders paint a striking picture. Sam Altman expects AGI by 2025, Dario Amodei by 2026-2027, and Elon Musk by 2026. Metaculus forecasters now average a 25 per cent chance of AGI by 2027 and 50 per cent by 2031—a dramatic acceleration from just a few years ago when the median estimate was 50 years away.

What makes these predictions particularly sobering for our industry is that 79 per cent of conversations on specialised coding agents like Claude Code already involve automation rather than augmentation. We’re not talking about a distant future—we’re witnessing the early stages of this transformation today.

The current reality: AI’s growing footprint in development

The data tells a compelling story. By 2027, 50 per cent of software engineering organisations will utilise AI-powered platforms to measure and increase developer productivity, up from just five per cent in 2024. Generative AI is already capable of automating 60-70 per cent of coding tasks, and more than 97 per cent of developers across four countries report using AI coding tools at work.

However, this isn’t simply about job displacement. While AI can automate many programming tasks, up to 80 per cent of programming jobs will remain human-centric. The key insight is that roles are evolving, not disappearing—at least not yet.

Five business model transformations for the AGI era

From code factories to intelligence orchestrators

Traditional software development companies that operate as “code factories”—taking specifications and converting them to working software—face existential risk. AGI will excel at this linear transformation. Instead, successful companies must become intelligence orchestrators, focusing on:

Problem architecture: Breaking down complex business challenges into solvable components
AI system design: Orchestrating multiple AI agents to work together effectively
Human-AI workflow optimisation: Designing processes where human creativity amplifies AI capabilities
Quality assurance and validation: Ensuring AI-generated solutions meet business and ethical standards

At DigiEx Group, we have begun to see this shift in our work as well. Our most successful projects now involve designing AI ecosystems rather than writing individual applications.

Also Read: SaaS revolutionises finance: From streamlining to AI integration

Platform-centric value creation

The future belongs to companies that build platforms enabling AI integration rather than point solutions. We’re approaching a transition to “Services-as-Software” where AI-driven solutions offer the capabilities of traditional service providers but operate entirely through software.

This means shifting from:

Custom development contracts → Platform subscription models
Project-based revenue → Outcome-based revenue sharing
Technical implementation → Business transformation consulting

The rise of hybrid intelligence ventures

By 2030, AGI is projected to contribute significantly to digital economies, with companies needing sustained engagement with specialised AGI startups through corporate venture capital and innovation hubs. The winning model combines:

Human intuition and creativity for strategic direction
AI processing power for execution and optimisation
Continuous learning loops where human feedback improves AI performance
Ethical oversight ensuring responsible AI deployment

Vertical AI specialisation

European opportunities lie in developing smaller, specialised models that can be curated with proprietary data sets, including Retrieval Augmented Generation (RAG), edge implementations, and AI agents tailored for specific industry needs.

The same principle applies globally. Rather than competing with AGI on general capabilities, software companies must become domain experts, offering:

Industry-specific AI solutions with deep vertical knowledge
Proprietary data advantages that AGI cannot replicate
Regulatory and compliance expertise for highly regulated industries
Cultural and regional customisation that global AGI solutions cannot provide

The talent ecosystem model

Vietnam produces 50,000 IT and engineering graduates annually, providing a strong talent pool for the AI industry, but the nature of required skills is rapidly evolving. Companies must transform from talent utilisers to talent developers, creating:

AI-Human collaboration training programs
Continuous upskilling ecosystems
Cross-functional teams combining domain expertise with AI capabilities
Innovation labs where human creativity meets AI processing power

Also Read: From 5 to 50: How agentic AI lets startups operate like enterprises

Regional advantages: The Vietnam opportunity

AI adoption could add an additional US$79.3 billion to Vietnam’s GDP by 2030, representing around 12 per cent of current economic output. Vietnam ranks second in Southeast Asia for AI startups, with Vietnamese AI startups receiving US$80 million in private funding in 2024—an eight-fold jump from 2023.

This creates unique opportunities for firms in the region:

Cost arbitrage remains relevant even in an AGI world, particularly for human oversight and creative problem-solving
Cultural and linguistic specialisation becomes more valuable as AGI struggles with nuanced, context-dependent solutions
Government support for AI development creates favorable business conditions
Talent density in technical fields provides competitive advantages in human-AI collaboration

Investment implications

In Q3 2024, half of all venture capital investment in the US went to AI, up from 15 per cent in 2017. AI and machine learning deals captured 46.4 per cent of US venture capital funding in 2024, up from 36.0 per cent the previous year.

For investors evaluating software development companies, the key questions are:

How are they preparing for AGI-assisted development?
What proprietary advantages will remain relevant?
How are they transitioning from labor-intensive to intelligence-intensive models?
What platform capabilities are they building?
How are they developing human-AI collaboration expertise?

Also Read: From automation to Agentic AI: Trust starts at the data layer

The strategic imperative: Act now

By 2027, the effects of AI on the world really start to compound, with AI-accelerated AI R&D causing exponential improvements. Companies that wait for AGI to arrive before adapting their business models will find themselves obsolete.

The transformation requires:

Immediate investment in AI-augmented development capabilities
Strategic partnerships with AI research organisations and startups
Workforce retraining programs focusing on human-AI collaboration
Business model experimentation before market pressure forces change
Platform development that can scale with AI capabilities

Conclusion: Embracing the intelligence revolution

The arrival of AGI will mark the end of software development as we know it—but it also represents the beginning of something far more powerful. Companies that successfully navigate this transition will not just survive; they will unlock unprecedented value creation opportunities.

At DigiEx Group, we’re focusing on building the infrastructure, partnerships, and capabilities needed for this next era—while sharing what we learn with the wider ecosystem. The question for every software company is not whether to adapt, but how quickly they can evolve from code creators to intelligence orchestrators.

The AGI revolution is coming. The only question is whether you’ll be ready to lead it or be left behind by it.

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