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    Home » Sections » Enterprise software » Build or buy software? AI is rewriting the answer

    Build or buy software? AI is rewriting the answer

    Promoted | AI is reshaping the buy-versus-build decision in financial services. The question is no longer as binary as it sounds.
    By BBD12 August 2026
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    Build or buy software? AI is rewriting the answer - BBD Software

    Organisations must decide whether to build their own systems, buy existing solutions or combine the two. Off-the-shelf platforms offer proven functionality and speed. Bespoke solutions can deliver greater control and customisation. Increasingly, enterprises are taking a hybrid route, working with specialist partners to create scalable solutions.

    “What we’re seeing with our clients is that everybody’s experimenting, everybody’s learning and everybody’s growing,” says Matthew Barnard, executive director at BBD Software. “The difficulty is that what you learned two weeks ago has already been replaced, and will be replaced again in two weeks’ time. But you can’t be a bystander on this journey; you need to get involved with it.”

    There is no universal answer. The right choice depends on context, regulation and where technology can create real advantage.

    Counting the comparative costs

    AI has lowered the barriers to building software. Organisations can customise open-source models and use AI-assisted development to prototype and iterate faster.

    Vibe coding, where developers use natural language to prompt AI tools to generate and refine applications, has made projects once considered too expensive or time-consuming more achievable. In financial services, it is even shifting the economics of legacy modernisation.

    Barnard points to Cobol systems still widely used across banks. Projects that once took years to rewrite are becoming more viable. “Some of the estimates we’re putting in to clients are half the price of what they would have been three years ago,” he says.

    Theodora Lau, founder of Unconventional Ventures and author of Banking on (Artificial) Intelligence, argues that the shift will force software providers to rethink pricing when organisations need only part of a SaaS product’s functionality.

    Cheap to build, hard to run

    But cheaper, faster development does not remove the complexity of getting enterprise software into production.

    Custom builds still require governance, maintenance and security. In financial services, accuracy is non-negotiable. Barnard notes that SaaS platforms contain years of embedded knowledge and intellectual property that cannot simply be recreated through faster coding.

    Lau agrees. “You’re dealing with people’s money, and you’re dealing with regulators. You can’t be 90% right, you have to be 100%.”

    Where differentiation actually lives

    The strongest case for customisation may lie where organisations genuinely differentiate. Barnard and Lau argue that highly regulated core systems, such as payments and accounting, will remain standardised. Customer-facing experiences offer more room for innovation.

    “Enterprises should think about where they see the technology as an advantage,” says Barnard. “They’re looking to do something unique that their competitors haven’t done, and that’s more often in the front-end interaction with customers rather than in the back-end accounting systems, which are based on international standards.”

    The first 90% of a solution can now be built quickly, Barnard says. The final 10% is where much of the work sits: running it in production, scaling it, supporting it and maintaining it.

    Lau makes a similar case for human oversight. AI can automate document-heavy processes or assist lending decisions, but organisations must be able to trace how decisions were made.

    Opening up to an agentic future

    The next major shift is towards agent-based systems. As AI becomes embedded in development and decision-making, organisations will need to move beyond ad hoc experimentation towards governance, repeatability and accountability.

    Regulators are already paying closer attention. The EU AI Act imposes strict obligations on high-risk systems, while the US and UK are taking different approaches. Lau expects stronger demands for audit trails, explainable outcomes and evidence of risk mitigation as agentic commerce grows. Firms will also need to know what agent is initiating a transaction, what it is authorised to do and how it is validated.

    For Barnard, the pace of change makes long-range certainty difficult. “It’s hard to look 12 or 18 months ahead because things are changing every month,” he says. “I think it’s best to take it quarter by quarter, and you need to be on that journey of actually learning and growing.”

    BBD is experimenting with specialised AI agents that can replicate elements of the work done by developers, business analysts and project managers. “And then we’re orchestrating those agents to do various tasks, and doing so carefully because, at the enterprise level, you can’t be nearly right – you have to be very right,” Barnard says.

    Watch the full podcast.

    About BBD
    BBD is an international provider of bespoke software solutions, with four decades of technical and domain expertise across the education, financial services, insurance, gaming, telecommunications and public sectors. It employs more than 1 200 IT professionals, drawing flexible teams from hubs in South Africa, India, the Netherlands, Portugal and the UK. BBD is 51% black-owned and a level-1 B-BBEE contributor with a 135% recognition level.

    • Read more articles by BBD on TechCentral
    • This promoted content was paid for by the party concerned
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    BBD BBD Software Matthew Barnard Theodora Lau Unconventional Ventures
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