In 2025, tech startups across the continent attracted around $4.1 billion in combined equity and debt, with the fintech segment still the largest equity segment. In short, there is a significant opportunity in a market that’s far from saturated.

There are, says McKinsey, a plethora of untapped opportunities that include cross-border payments, SME lending and embedded, sector-specific solutions.

However, says Mandla Mbonambi, CEO of Africonology, fintech innovation is outpacing the sector’s ability to plug it into old systems.

“As a result, the real constraint to change has become integration,” he continues. “Legacy systems were not designed for real-time, API-driven products and data is scattered across channels and back-office systems, limiting personalisation and cross-sell opportunities, as well as governance, security and efficiencies.”

While on the one hand, the market has depth, velocity, and real-world relevance, on the other, it is entering a complex phase of growth in which its essential fintech integration is being implemented correctly. And this is where the real bottleneck now sits.

As instant payments, digital wallets, embedded finance and platform-based services accelerate, many companies are still trying to push modern experiences through ageing core banking systems, fragmented data estates and integration layers held together by workarounds.

Banks, mobile money operators, remittance companies and fintechs are increasingly offering new ways of banking and accessing funds, particularly around cross-border payments. Still, these solutions are also fragmented with high costs and delays.

“This is not a pressure unique to Africa,” says Mbonambi. “But it is particularly important here because the continent has moved so rapidly in financial innovation. If Africa wants to continue leading in this sector, integration has to become a strategic priority. Legacy system integration is a persistent obstacle, with challenges that include poorly managed data migration, incompatible system architectures, and insufficient testing protocols.”

Companies need a strategic framework that aligns technology investments with business objectives while still ensuring smooth integration across the enterprise. Innovation at the front end has become relatively easy to showcase. A new lending feature, a smarter onboarding

journey, a slicker payments interface, and an AI-driven customer layer are visible wins. The harder work happens underneath, where systems need to talk to one another cleanly and reliably.

MuleSoft’s 2025 Connectivity Benchmark shows how widespread this issue has become: the average enterprise now runs 897 applications, yet only 29% are integrated, and 90% say data silos are creating business obstacles.

With IT teams spending close to 40% of their time designing, building, and testing custom integrations, it’s clear that integration debt has become one of the biggest brakes on digital and AI initiatives.

“You need processes that make sense, clean data and people who understand both the business and the technology. If you skip these steps, you’re just building an expensive way to make mistakes,” says Mbonambi. “Solving for these incoming bottlenecks translates into four immediate priorities: legacy modernisation, API enablement, integration as a service and platform expertise.”

Core systems do not always need to be ripped out. Still, they do need to be re-architected so old and new can coexist with less friction because careful integrations can allow old and new systems to coexist while protecting prior investments.

API-led connectivity gives institutions a more flexible way to expose services, connect partners, orchestrate data flows and reduce the dependence on brittle point-to-point integrations.

“Composable enterprise architectures built on API-led connectivity can reduce integration costs by 30% while creating reusable building blocks for innovation,” says Mbonambi.

The third step is integration as a service to ensure organisations have integration capability embedded into delivery from the start, which is supported by governance, testing and visibility. Then, platform expertise wraps all the factors into a cohesive whole, providing a deep understanding of the business ecosystems and how to bring them together coherently.

“Africa has already shown that it can lead in mobile money, digital payments and financial access,” concludes Mbonambi. “The next step is less glamorous, it’s process, process, process because the winners in fintech’s next chapter will be the ones that can connect core banking, customer channels, partner ecosystems and data in ways that are secure, scalable and commercially sustainable.”

Today, however, despite a growing need for agile and efficient testing, legacy QA models are struggling to keep up with cloud-native environments, fragmented teams and rapid release cycles.

And this, says Mandla Mbonambi, CEO of Africonology, introduces a new era of software testing using AI and automation to prioritise tests and analyse vast quantities of data. It is also, he says, introducing quality, security and governance risks.

“The benefits of AI in testing automation and QA are that it allows teams to move incredibly rapidly,” he says. “Companies benefit from faster automation processes, and their productivity increases exponentially. AI is also capable of analysing the data to detect defects or coverage gaps, and it can provide teams with high-risk scenarios or recommend additional tests based on its analyses.”

The Capgemini World Quality Report 2024-2025 was quick to highlight the impact of AI on the industry, emphasising its ability to optimise test coverage, reduce human error and introduce intelligent automation.

The study found that an impressive 68% of companies are using AI, with 72% reporting faster processes as a result.

The technology is changing the testing story, moving it away from an after-the-fact process that discovers unexpected errors and frustrates teams and deadlines alike. AI enables testing in near real time as models continuously analyse code throughout the development process, and they can be integrated into development and operations from the outset.

“AI models can learn, they can predict errors that crop up regularly or where they’re most likely to occur,” says Mbonambi. “They turn testing into a smoother part of the process, making it proactive and immediate instead of reactive and defined by ticking boxes. They also allow for self-healing, where the automation can detect when a test will break, find a resolution, and then apply the update so the test still passes if the business behaviour remains valid.”

Self-healing has the potential to minimise failures caused by minor changes and reduce the monotony burden on testing teams – talented humans now have more time to prioritise exploratory testing or more complex tasks.

The technology gives people the space to become high-quality architects, defining risk models, guiding AI, and interpreting patterns, rather than just running tests.

“There are agentic platforms that now can take on a lot of the heavy testing grunt work with minimal human input, capable of acting almost like testing interns that fortunately don’t get tired or frustrated,” says Mbonambi. “It sounds too good to be true, which unfortunately it can be – while AI has immense value in the QA environment, it also introduces risks that have to stay top of mind.”

Just as AI in the workplace tends to hallucinate or overcompensate, the same risks apply in testing. Some of the most common problems include false positives and false negatives, which add to testing noise rather than minimising it, an over-reliance on automation that impacts skills and awareness, and data privacy and security.

Then there’s the reality that AI models are still black boxes – teams don’t have visibility into the AI decision-making process and don’t know why some tests are prioritised while others are not.

“Bias, security, private information, limited guardrails and governance that’s battling to keep up with the pace of change, are very real concerns when it comes to introducing AI into the testing environment,” says Mbonambi. “Right now, as teams learn how to use and optimise AI in testing better, it’s important to remember it is a tool designed to augment the process. People are needed to validate AI output and make release decisions and, very importantly, become the guardrails for data privacy and explainability.”

This doesn’t mean AI is too risky, just as it doesn’t mean AI is the perfect solution to every testing problem.

Right now, AI is as much in its infancy as its use cases, which means testing with AI models and tools should be considered and balanced. Humans are essential, but so are the tools that lift the burden of complexity and deadlines.

Mandla Mbonambi, Africonology’s CEO, asserts that in this dynamic intersection, cybersecurity professionals stand at the forefront, leveraging GenAI’s capabilities to fortify defences against unprecedented threats and seize unparalleled opportunities.

“Our emphasis is on seamlessly integrating Generative AI into cybersecurity frameworks, ushering in a new era of digital protection. Our team’s extensive experience in deploying AI algorithms to analyse extensive datasets, detect code vulnerabilities, and thwart malware threats positions us as innovators in the evolving GenAI and cybersecurity landscape.”

There is an intricate relationship between GenAI and cybersecurity that is both captivating and challenging.

Mbonambi highlights the continuous evolution of AI-driven attack vectors, such as multilingual phishing and sophisticated deepfakes, urging cybersecurity professionals to explore GenAI for advanced threat detection and response capabilities.

Addressing the dual nature of GenAI, Mbonambi underscores the importance of attracting and retaining top-tier talent.

“Africonology’s commitment to a dynamic work environment and cutting-edge technology training programs ensures our team remains at the forefront of the rapidly changing cybersecurity landscape.”

As the digital frontier advances, staying ahead of adversarial tactics while embracing innovative defence mechanisms is paramount. Mbonambi advocates for optimism while acknowledging the risks associated with GenAI.

“We must always emphasize responsible and ethical use to keep GenAI as a tool under human supervision rather than a potential adversary.”

In this ever-evolving landscape, Mbonambi encourages a strategic mindset to navigate the opportunities and challenges presented by the convergence of GenAI and cybersecurity.

“As technology advances, the fusion of human expertise and AI capabilities becomes the linchpin for securing a digital future that is both resilient and transformative.”

Organisations must also adapt to the transformative impact of generative AI or risk being unprepared to defend against emerging threats.

Mbonambi underscores several considerations for enterprises incorporating generative AI into their operations.

“Security leaders cannot solely prioritize the impact on their security teams; the ripple effect extends to workflows across various enterprise functions,” he says.

To counter potential risks associated with the unauthorized use of generative AI, security teams need to go beyond natural language processing and develop skills in prompt security engineering.

With companies relying on vendors for generative AI solutions, security professionals must evolve their third-party risk management approach, addressing the inherent complexities and posing targeted questions regarding supply chain security and risk management.

“Embracing generative AI requires deploying modern security practices. Existing cybersecurity technologies, such as API security and privacy-preserving technologies, offer valuable controls to secure the adoption of generative AI,” says Mbonambi. “Proactive consideration of procedural gaps related to data leakage, data lineage, observability, and privacy is crucial for ensuring comprehensive security measures.”

As generative AI becomes integral to the digital landscape, Mbonambi concludes that security leaders must adopt a forward-thinking approach.

“They must embrace change and actively participate in developing security strategies that safeguard against evolving threats. The collaboration between security professionals, technology providers, and enterprises is pivotal in shaping a secure and resilient future.”

Although the percentage has dropped from 70% in 2022 to 54% in 2023, there remains a need for organisations to find people who can plug the holes with skills that are relevant and revolutionary because the cost to the business is too high.

IDC found that the skills gap cost is more than $6,5 trillion in missed product releases, poor competitiveness, and lower customer satisfaction.

Mandla Mbonambi, CEO of Africonology believes that companies need to find a better way of creating a talented workforce that allows both organisation and employee to thrive.

“Focusing on the people you have within your business and providing them with the opportunity to upskill or reskill is a smart move,” he continues. “Adopting a skills-based approach means your employees are receiving the support and development they need to thrive within your organisation. It also means you are creating skills pathways that allow employees to move into other roles that may be more urgent or relevant to the company. By allowing for ongoing skills and employee development, you are building a talented workforce that is agile, engaged and committed.”

The skills-based approach is also a way of creating a more agile workforce which is far more sustainable for the organisation as you can now fit employees to the demand.

As IDC says, a holistic culture of learning is important and this is echoed by the World Economic Forum (WEF) which states that a skills-first approach can improve diversity, upward mobility, flexibility and employee retention.

It provides employees with a road to better positions within the organisation, positions they may have not been eligible for, or even thought of applying for, and it allows for companies to access talent that previously may have been overlooked.

“A skills-based approach is a smarter way of resolving the talent crunch,” says Mbonambi. “In addition to filling gaps in the business and reducing the cost of talent limitations, it allows you to create a relevant, skilled workforce. These individuals may not have degrees or have gone to a university, but they have proven their abilities in coding, DevOps, security or AI. By providing them with additional training and support, they become invaluable assets to your business.”

Companies have already shown a trend towards becoming more reliant on non-traditional workers for skills and roles that are considered high-value.

A Deloitte analysis back in 2022 identified the trend. It highlighted how it is an approach that places value on a person’s ability to learn and grow rather than on how many certificates they own.

Again with Deloitte, in another analysis of workplace trends, the company found that companies are becoming more reliant on non-traditional workers for skills and roles that are considered high value and of strategic importance. It is a forward-thinking approach that puts value on a person’s ability to learn, grow and engage in continuous professional skills development rather than on their status.

“Companies need to capture and hold the right talent,” says Mbonambi. “Organisations will likely lose people who want more autonomy and flexibility if they don’t offer skills development pathways and internal opportunities.”

The same principle applies to collaborating with a third-party company that specialises in high-end DevOps or security.

Is your service provider taking a skills-based approach to the development of its talent? The best people should be working on your projects because the company has attracted a wide range of people who fill the roles with expertise and talent.

This is particularly true of highly complex and in-demand skill sets such as DevOps. Having access to an exceptional talent pool of people who have the opportunity to constantly evolve their abilities and expand their knowledge is a huge relief for companies that are facing high costs (in-house DevOps can be expensive) and slow transformation journeys thanks to limited skills and DevOps complexity.

“Attracting and finding skilled people should be a part of a DevOps company’s skill set,” concludes Mbonambi. “If the organisation isn’t capturing the attention of well-rounded and skilled individuals, then it isn’t going to meet your DevOps needs. So, perhaps the biggest skills trend for 2024 isn’t the type of skills that are needed, but rather how companies nurture and capture those skilled individuals.”

Moving into a year fractured by politics, economics and complicated market conditions, it’s time to ditch the traditional and hard-bitten approaches to talent and instead embrace the potential of skills-based service delivery within an organisation that puts expertise ahead of paper.

Helping organisations to optimise processes and save costs, outsourcing has evolved alongside the market and enterprise expectations. It is now smarter, says McKinsey, as companies outsource to ‘capitalise on more sophisticated provider offerings’ and thereby open their corporate doors to advanced digital solutions such as AI, robotics, automation, analytics and machine learning.

It also, reminds Mandla Mbonambi, CEO of Africonology, of a strategic way for organisations to remain focused on their core business operations and activities while trusting services and solutions to the capable hands of a trusted service provider.

“Outsourcing can be an invaluable asset,” he continues. “However, it needs to be approached with realism. No solution or service is without its pros and cons, and outsourcing is no different. For an organisation to benefit from an outsourcing partnership, it needs to understand both the benefits and the drawbacks of this approach to ensure value is created.”

The benefits are significant and long-term, particularly if the relationship between the service provider and the company is solid.

Then, benefits such as lower labour costs and reduced labour risks, will be felt by the organisation over the long term.

When a company opts into outsourcing from a service provider to undertake specific tasks, it doesn’t need to hire permanent consultants or skilled employees to bolster its capabilities.

Instead, the service provider steps in with a full crew complement populates short- and long-term projects with the right talent and removes the risks that accompany the management, hiring and engagement of staff.

“The company outsourcing the work doesn’t have to worry about employment benefits, packages or retention, they just hand those problems over to the service provider,” says Mbonambi. “This approach also allows for organisations to focus more on the core of their business while non-core, yet essential, roles and projects are managed externally within specific timelines and budgets.”

Wedded to the management and retention of talent is the delightful benefit that the company no longer has to wade into the battle ring and fight for top-tier talent. Instead, specialised, highly skilled and experienced talent is wooed and curated by the service provider while the company gets all the value from having hands-on access to a smart and capable workforce.

However, stepping into the world of outsourcing does ask that both the service provider and company are aware of the risks.

Sensitive data can be tricky to manage within the context of outsourcing – how should this data be handled by a third party, especially if they’re offshore?

What about the risk of intellectual property? Despite the proliferation of non-disclosure agreements and contracts designed to mitigate this risk, it doesn’t take away the potential for someone to share this information with someone else.

“These are considerations that must be prioritised before stepping into an outsourced relationship,” says Mbonambi. “They will add to the security costs required to protect sensitive data and demand that companies create solid and open channels of communication designed to reduce the risks of information leakage and loss. That said, communication can also be a catch point as some outsourced companies may not share the same culture or language and this can affect the relationship and add to the risks.”

Finally, one of the challenges that needs to be considered by both parties when moving into an outsourced relationship is the contractual agreement.

This includes Non-Disclosure Agreements binding both parties in handling all activities and materials confidential.

These can be rigid and complicated and can require that companies follow stringent legal processes before making any changes or shifting in a new direction.

“This doesn’t mean that outsourcing is going to end up being a complicated tangle of terms and conditions,” concludes Mbonambi. “Understanding the risks and recognising the benefits allows for both company and service provider to approach their relationship intelligently and with transparency. Open communication, clear visibility into services and expectations, agility and flexibility baked into the relationship to allow for shared growth and understanding – these are all key to building a relationship within the outsourced model that will thrive long after the ink has dried.”