Venture money is flooding into AI shopping agents. Payment networks, browser makers and AI labs are racing to define how autonomous agents will shop, compare and buy. Specno, the product consulting firm that helps companies de-risk complex software builds, says the infrastructure behind that race isn’t keeping pace with the capital. Trust, verification and accountability are still unsolved, and the technology is moving faster than the answers.

“Hey Agent, find me the cheapest one”

The shift Specno expects: people stop browsing and start delegating. Instead of opening an app, a consumer tells an agent what they want. “Find me the cheapest kettle.” “Match these blinds to this photo.” “Furnish this room to this budget.” The agent searches, compares and buys. The person never touches a storefront.

“The interface of the future isn’t a search bar. It’s a conversation,” said Joshua Harvey, CEO of Specno. “People are going to stop browsing and start delegating. They’ll tell their agent what they want, show it a photo, give it a budget, and expect it to come back with the right thing already found or bought. That’s a different relationship between a brand and a customer, and most retailers haven’t touched their systems to account for it.”

SEO is being rewritten for machines

If agents do the shopping, retailers need to be visible to agents, not just to people. That means structured, machine-readable product data, pricing feeds that update in real time, and content built for an AI working through hundreds of options in seconds, not a person scrolling a page.

Ranking well in human-facing SEO today guarantees nothing with an AI agent evaluating on different criteria. Specno expects a new discipline, agentic SEO or answer-engine optimisation, to matter as much to commerce as search ranking has for the last 20 years.

Who’s liable when the agent gets it wrong?

Then there’s the harder problem nobody has answered. If a shopping agent gets fooled by a fake storefront and completes the purchase, who’s responsible? The consumer? The agent developer? The payment provider? The platform that surfaced the fake listing?

“Right now, if someone gets scammed online, there’s a clear chain. You know who clicked the button and who authorised the payment,” said Harvey. “Once an agent makes that call for you, the chain breaks. Did the agent fail to verify the site? Did the marketplace fail to flag it? Did the buyer even see what was purchased before it happened? Nobody has answered that, and it will matter a lot more once agents are transacting at scale, not just browsing.”

Specno believes the winners in this category will treat verification, fraud detection and liability as core product features from day one, not something patched on after agentic transactions go mainstream.

“This isn’t a problem you solve with a bigger team,” said Harvey. “It’s a problem you solve with the right specialist who holds the technical, commercial and regulatory picture at once, moving fast enough to build the trust layer before the fraud does. That’s the model we’ve built Specno around, and it’s exactly the kind of build this category needs right now.”

Specno is already helping retailers and product teams get ready by structuring product data for AI discovery, designing conversational and visual-search experiences, and building the verification and trust layers agents need to transact safely.

The post Who’s Actually Shopping? Specno on the Infrastructure Agentic Commerce Still Doesn’t Have appeared first on Tech Scene ZA.

Venture money is flooding into AI shopping agents. Payment networks, browser makers and AI labs are racing to define how autonomous agents will shop, compare and buy. Specno, the product consulting firm that helps companies de-risk complex software builds, says the infrastructure behind that race isn’t keeping pace with the capital. Trust, verification and accountability are still unsolved, and the technology is moving faster than the answers.

“Hey Agent, find me the cheapest one”

The shift Specno expects: people stop browsing and start delegating. Instead of opening an app, a consumer tells an agent what they want. “Find me the cheapest kettle.” “Match these blinds to this photo.” “Furnish this room to this budget.” The agent searches, compares and buys. The person never touches a storefront.

“The interface of the future isn’t a search bar. It’s a conversation,” said Joshua Harvey, CEO of Specno. “People are going to stop browsing and start delegating. They’ll tell their agent what they want, show it a photo, give it a budget, and expect it to come back with the right thing already found or bought. That’s a different relationship between a brand and a customer, and most retailers haven’t touched their systems to account for it.”

SEO is being rewritten for machines

If agents do the shopping, retailers need to be visible to agents, not just to people. That means structured, machine-readable product data, pricing feeds that update in real time, and content built for an AI working through hundreds of options in seconds, not a person scrolling a page. 

Ranking well in human-facing SEO today guarantees nothing with an AI agent evaluating on different criteria. Specno expects a new discipline, agentic SEO or answer-engine optimisation, to matter as much to commerce as search ranking has for the last 20 years.

Who’s liable when the agent gets it wrong?

Then there’s the harder problem nobody has answered. If a shopping agent gets fooled by a fake storefront and completes the purchase, who’s responsible? The consumer? The agent developer? The payment provider? The platform that surfaced the fake listing?

“Right now, if someone gets scammed online, there’s a clear chain. You know who clicked the button and who authorised the payment,” said Harvey. “Once an agent makes that call for you, the chain breaks. Did the agent fail to verify the site? Did the marketplace fail to flag it? Did the buyer even see what was purchased before it happened? Nobody has answered that, and it will matter a lot more once agents are transacting at scale, not just browsing.”

Specno believes the winners in this category will treat verification, fraud detection and liability as core product features from day one, not something patched on after agentic transactions go mainstream.

“This isn’t a problem you solve with a bigger team,” said Harvey. “It’s a problem you solve with the right specialist who holds the technical, commercial and regulatory picture at once, moving fast enough to build the trust layer before the fraud does. That’s the model we’ve built Specno around, and it’s exactly the kind of build this category needs right now.”

Specno is already helping retailers and product teams get ready by structuring product data for AI discovery, designing conversational and visual-search experiences, and building the verification and trust layers agents need to transact safely.

The post Who’s Actually Shopping? Specno on the Infrastructure Agentic Commerce Still Doesn’t Have appeared first on Tech Scene ZA.

South African businesses have become highly effective at producing software quickly. What remains far less clear is why this increased engineering velocity is failing to translate into commercial growth for many companies.

That is the central finding of the 2026 State of Product Development Report, released this month by Cape Town-based digital product consultancy Specno. The report outlines the 10 capabilities now defining how scaling product teams turn digital products into revenue, and names the widening performance gap between companies that ship features and those that actually compound revenue growth.

Specno’s 2026 State of Product Development Report finds that top-performing teams ship 30%  to 50%  less than their peers yet grow significantly faster.

The report draws on insights from a council of group CEOs and senior product operators, observed performance patterns across hundreds of embedded engagements, and field-tested applications inside live product teams across the emerging-market landscape. Collectively, those engagements span organisations responsible for billions of rand in annual economic activity, including regulated financial institutions and pension funds, FMCG and food businesses, logistics operators, venture-backed fintechs scaling across South Africa and the broader African continent, marketplaces and enterprise digital platforms. This is not a survey; it is a benchmark built from direct operational exposure.

The findings arrive at a critical inflection point for South Africa’s digital economy. Businesses across fintech, SaaS, logistics, marketplaces, and digital services are facing a fundamental shift: artificial intelligence has collapsed the cost of building software, meaning that shipping velocity is no longer a competitive moat. In fact, one fintech profiled in the report runs its build operation on more than 900 AI agents and 173 connected tools, turning a voice note into a compliant plugin from a near-empty prompt. 

When building becomes that cost-effective, the constraints move from production to decision-making, and most teams are still investing heavily in the part that machines already do.

One of the report’s more striking conclusions is that the strongest teams have quietly shifted from a build culture to a review culture. As AI continues to drive the cost of production towards zero, competitive advantage no longer comes from writing more code, but from exercising better judgement about what should be built, what should be rejected, what deserves prioritisation, and how work should be sequenced. Increasingly, AI handles the production while humans provide the critical oversight, challenging assumptions, reviewing outputs, and making the decisions that shape successful products.

“The market has become very good at measuring output,” says Joshua Harvey, CEO at Specno. “What many businesses still struggle to measure is whether the systems underneath that output are mature enough to sustain growth effectively over time. The bar for turning product into revenue has risen sharply in the last 24 months. Capital is harder to raise. Compounding it is harder still. The gap between teams that compound their gains and those that stall continues to widen with each passing quarter.”

According to the report, one of the biggest misconceptions in modern product development is that shipping more software creates more growth. In practice, the opposite often proves true. The highest-performing product teams observed by Specno shipped 30% to 50% less at the Minimum Viable Product (MVP) stage than their peers, yet consistently outperformed them commercially. They converted engineering effort into revenue at two to three times the industry average, responded to market signals an order of magnitude faster, and treated every product decision as a measurable commercial bet rather than another feature release. Their roadmaps were not longer. They were just deliberate.

The report identifies Product Decisioning as the weakest capability across the market, a pattern confirmed at both ends of the maturity curve. One example involved a premium direct-to-door seafood business turning over several million rand a month while making daily pricing decisions on instinct rather than customer evidence. Another was a funded startup that scored lowest on evidence and validation in its own assessment. Neither had a product problem first. 

The report introduces what Specno calls the “Product-to-Revenue Capability Stack,” a three-layer model covering Product Decisioning, Delivery Velocity, and Revenue Conversion. The report identifies 10 core capabilities that consistently distinguish high-performing, compounding product teams from those that stall, regardless of industry, business model, or stage of growth.

Specno’s Product-to-Revenue Capability Stack

“We developed this report because we realised there was no structured way for businesses to properly evaluate the maturity of their product environments,” says Harvey. “After working alongside organisations ranging from regulated financial institutions and pension funds to fast-growing fintechs, FMCG businesses and enterprise platforms operating across Africa, the same capability patterns kept emerging. Many tools measure isolated technical outputs, but very few assess whether the wider operational environment supporting a product is actually capable of sustaining long-term growth. Most product teams are operating below the standard the market now demands, and they can feel it without being able to name it.”

For South Africa’s fintech operators, SaaS founders, logistics platforms, and enterprise product leaders, the implications are direct. The report argues that AI is not a standalone capability but table stakes, an amplifier that makes weak capabilities more visible and strong capabilities faster and more scalable. The question in 2026 is not whether a team uses AI, but whether they use it to operate at a higher level across the capabilities that actually drive revenue.

“One of the things we realised very quickly is that there is still very little shared industry insight into what operational pressure inside scaling digital businesses actually looks like,” closes Harvey. “We believe there is real value in consolidating that information in a way that helps businesses better understand the 

patterns, capability gaps, and operational risks emerging across the market. The teams that win in 2026 are not the ones doing more. They are the ones building the capabilities that matter, and knowing exactly how strong they are.”

The full 2026 State of Product Development Report is available here 

The post New report reveals South African businesses don’t have a software problem…. They have a judgment problem appeared first on Tech Scene ZA.

Specno says many scaling companies still lack visibility into whether the systems underneath their digital growth are operationally prepared for long-term scale

South African businesses have become highly effective at digitising quickly. What remains far less clear is whether the systems underneath that growth are actually built to sustain it.

That is the premise behind a new initiative launched this month by Specno, which has introduced what it describes as South Africa’s first structured digital product readiness benchmark aimed at measuring the operational maturity of scaling digital businesses.

The initiative forms part of the company’s newly launched “Fix My Product Month” campaign, through which participating businesses complete structured product assessments designed to identify hidden weaknesses across product operations, delivery systems, governance structures, and commercial execution.

The campaign comes at a time when businesses across sectors, including fintech, SaaS, logistics, marketplaces, and digital services, are facing increasing pressure to scale platforms, integrate technologies, accelerate delivery cycles, and improve customer experience, often simultaneously.

According to Specno, many organisations have become sophisticated at measuring outputs such as growth, platform usage, sprint velocity, customer acquisition, and revenue, while still lacking clear visibility into whether their broader digital operating environments are structurally resilient enough to support that growth over time.

“The market has become very good at measuring output,” says Joshua Harvey, CEO at Specno. “What many businesses still struggle to measure is whether the systems underneath that output are mature enough to sustain growth safely and effectively over time.”

The company says the idea for the assessment emerged after repeated exposure to similar operational patterns inside scaling businesses.

“We kept seeing businesses that were growing quickly externally, but internally there were ecurring signs of operational strain, fragmented delivery environments, unclear product accountability, or decision-making systems struggling to keep pace with scale,” says Harvey. “What became clear to us was that there was no real benchmark for measuring the operational maturity sitting underneath digital products in the South African market.”

Specno refers to the assessment as a “digital product dipstick”, a structured benchmarking tool designed to help businesses evaluate whether the environments surrounding their products are commercially aligned, operationally resilient, and capable of scaling sustainably.

The process begins with a detailed assessment completed by participating businesses before being reviewed by Specno’s product specialists, who then identify recurring operational weaknesses, delivery bottlenecks, product governance gaps, and broader growth risks.

Rather than focusing purely on technical performance, the initiative attempts to examine the wider organisational systems that influence whether digital products succeed or fail at scale.

“We developed the assessment because we realised there was no structured way for businesses to properly evaluate the maturity of their product environments,” says Harvey. “There are many tools that measure isolated technical outputs, but very few that assess whether the wider operational environment supporting a product is actually capable of sustaining long-term growth.”

The findings gathered throughout the “Fix My Product Month” campaign will contribute to The South African Digital Product Readiness Report, which Specno plans to release publicly in June 2026.

The report is expected to examine broader patterns emerging across South Africa’s scaling digital economy, including operational fragmentation, delivery pressure, product governance weaknesses, execution bottlenecks, and resilience gaps inside growing technology-driven businesses.

According to Specno, part of the motivation behind publicly releasing the findings is to contribute broader industry visibility into how South African digital businesses are actually operating behind the scenes.

“One of the things we realised very quickly is that there is still very little shared industry insight into what operational pressure inside scaling digital businesses actually looks like,” closes Harvey. “We believe there is real value in consolidating that information in a way that helps businesses better understand the patterns, capability gaps, and operational risks emerging across the market.” The South African Digital Product Readiness Report will be released publicly in June 2026 and made available to businesses, investors, founders, and industry stakeholders.

The post New benchmark aims to measure product readiness in SA businesses appeared first on Tech Scene ZA.

Building software is only getting cheaper. Building the wrong thing at scale has never been more expensive. That tension sits at the centre of Specno’s evolution from award-winning digital agency to product consultancy. 

The deliberate repositioning by the Cape-Town-based firm was the result of careful consideration, after noticing a significant gap in the local market. No one else is delivering specialist support to business professionals in the moment most growth-stage companies get wrong: when making decisions for business cases, which must later hold up in reality, and generate revenue.

“Across the South African tech landscape, a pattern has emerged. Companies with strong engineering teams are shipping on time, but the business case collapses after launch. Users aren’t converting. Daily active usage drops off. Features go live that nobody asked for. Revenue assumptions that looked solid in a deck don’t hold in reality,” shares Joshua Harvey, CEO at Specno.

His concern is that these challenges get treated as marketing problems: “These are product problems. Uninvalidated user journeys, untested architectural assumptions, and decisions that were approved in documents but never proven in real conditions. And it can come as a shell-shock after months of work, investment, and business fees. Without specialist support at this level, most businesses fold, and for the wrong reasons. We are repositioning ourselves to change that – to ensure more South African businesses and companies get to revenue, faster”.

Specno’s new model is built to intervene at that exact point. The company embeds senior product, UX, and engineering specialists directly into client teams during the delivery windows where the margin for error is smallest: platform builds, product launches, critical integrations, and architecture commitments that are hard to reverse.

Their work starts with a challenge, not execution. Specno’s clients typically arrive with decisions already made. “The work begins by pressure-testing those decisions before they become expensive: What to build, in which order, and exactly how to build it. That clarity, established before a line of code is written, is what makes the difference between a product that holds up after launch and one that ships into silence,” adds Harvey

Central to this is Specno’s Product Strategy practice, a structured process designed to strengthen decision quality before development begins. The output is not a recommendations document. It is a decision infrastructure, so that by the time development starts, every major product decision has already been made, tested, and signed off by the same team that will build it.

“Most product failures are not execution failures. They are decision failures that happened upstream,” comments Harvey. “The problem definition wasn’t stable. The assumptions weren’t tested. The technical risk wasn’t visible. The way the development roadmap was estimated  By the time teams discover these issues during delivery or in production, the cost of correcting them has already multiplied. That’s why our product strategy work starts before build, to surface those risks before cost and complexity lock in.”

The distinction from traditional consultancies is structural. Most firms separate the thinking from the build. One team writes the strategy. Another team designs it, and another delivers it. By the time recommendations reach execution, context is lost, assumptions go untested, and decisions get locked in before anyone proves they work. 

Specno runs both in one thread. The same team that challenges the roadmap executes against it. Product strategy, design, full-stack engineering, and AI infrastructure. No handoffs. No translation layer. Decisions get proven through delivery, not through documents.

“When you’re about to launch, commit to architecture, or scale what you’ve built, you don’t need more opinions. You need to know it works,” says Harvey. “That’s what we do. We run the riskiest decisions through real delivery conditions so that when our clients commit, they’re committing to something that’s already been tested.”

That embedded model also shifts the economics. By building AI into the development process from day one, the same team ships more without scaling headcount, resulting in shorter cycle times: “As AI drives down the cost of building software, companies are moving faster than ever. But speed without decision quality just means you arrive at the wrong answer sooner. Specno’s target clients are growth-stage and scale-up companies with capable teams who are shipping, but facing product and architecture commitments that are hard to reverse. These companies need senior product and engineering capability for their highest-risk initiatives, but not permanently. Specno fills that gap with embedded cross-functional teams that plug into existing structures without the overhead or handoff risk of traditional consulting,” concludes Harvey, with excitement.

The companies that survive the next few years won’t be the fastest shippers. They’ll be the ones who proved their decisions were right before they committed to them. That’s the bet Specno is making.

The post Cape-Town based digital innovation agency evolves to become Africa’s leading product consultancy firm, betting to solve challenges for scale-up’s with decision-making problems appeared first on Tech Scene ZA.

“With early projections from the Central Energy Fund pointing to increases in the region of R4,27 for 93 Unleaded, R4,74 for 95 Unleaded, and R7,83 for diesel in April, the economic argument for Electric Vehicles (EVs) has never been stronger” shares Joshua Harvey, CEO of Specno. 

Harvey recently spearheaded the development of a custom-built, end-to-end digital platform for a major national EV charging network, which is aiming to operate across hundreds of locations in South Africa. The project offered a clear view into a market that is evolving rapidly, and one that is now entering its next phase of maturity: “South Africa’s EV ecosystem has grown quickly, and much of the early technology was designed to establish access and reliability. Now, the opportunity exists to refine that experience for the local user, to wildly improve their experience and amenability to make the switch over to EVs” Harvey explains. 

Many of the foundational platforms originally used in South Africa to locate charging ports had been adapted from international markets, particularly Europe, where EV adoption is more mature, and the infrastructure landscape is fundamentally different. “In Europe, the challenge is abundance. There are more chargers than a user needs, so platforms are designed to filter and optimise choice,” says Harvey. “In South Africa, the context is different. Availability of charging stations is more limited, journeys are more deliberate, and user behaviour is not yet habitual. That requires a different kind of design thinking.” 

As the industry grows, so too do user expectations. Early systems prioritised functionality, ensuring that drivers could locate and access charging points reliably. The next step, designed for deployment across South Africa by Harvey and Specno specialists, is about removing friction from the experience itself: “This includes simplifying payment journeys, reducing the number of steps to initiate a charge, and ensuring users do not have to navigate multiple systems or pre-funded wallets” he adds. 

“None of these systems were built incorrectly. They were built for a different moment in time,” Harvey notes. “But as adoption grows, the expectation shifts. When you are asking someone to move away from a deeply ingrained behaviour like refuelling with petrol, the alternative has to feel effortless.” 

He argues that EV adoption is not driven by infrastructure alone. It’s shaped by how intuitive, seamless, and accessible the experience feels in everyday use: “Conversion is a product problem,” Harvey says. “And in the EV space, that product is not just the car or the charger. It is the entire journey around it.”

To solve this, Harvey and his cross-functional team at Specno approached the new platform with a philosophy of radical simplicity. Drawing inspiration from highly intuitive, single-action apps like Shazam and micromobility platforms such as Bolt, they completely rebuilt the user journey. “Our guiding mantra was ‘Find and Pay,’” says Harvey. “We stripped away everything unnecessary. The solution we built features a map showing real-time availability of chargers, and a central button that simply says ‘Tap to Start Charging.’ We eliminated the need for RFID cards and manual wallets by integrating Apple Pay and Google Pay. It’s instant, frictionless, and intuitive. This marks a new benchmark for simplicity in South Africa’s EV market.”

The African EV charging market, valued at just $31.93 million in 2022, is projected to expand to $256.53 million by 2030. Meanwhile, the average South African motorist living in a city can already save approximately R14,000 per year by driving an electric vehicle instead of a petrol model.

The long-term vision for South Africa’s EV infrastructure is closely linked to the country’s growing renewable energy sector. With Independent Power Producers (IPPs) investing heavily in wind and solar, particularly in the Northern Cape, which offers some of the strongest solar potential globally, there is a clear pathway to powering EV networks through cleaner energy and reducing reliance on global oil markets and their volatility within the next 5 years. 

However, to unlock this future, Harvey believes there is an opportunity for South African tech giants to continue raising the bar through digital design simplification. “Across sectors, from government e-services to major corporate banking platforms, we are seeing an increasing focus on functionality and feature depth,” Harvey explains. “The next step is refining how those features are delivered, ensuring that the experience remains intuitive and easy to navigate for the end user.”

He emphasises that simplicity should not be misunderstood as basic: “Simplicity is not a lack of sophistication. It is the outcome of deeply understanding a problem and doing the hard work behind the scenes so the user doesn’t have to,” he says. “South Africa has an incredible opportunity to design solutions that are grounded in our local context, while still being globally competitive. If we can prioritise seamless, user-first experiences, we will be well-positioned to support the transition to electric mobility and green energy in a meaningful way.”

The post The Middle East oil crisis is South Africa’s EV wake-up call  appeared first on Tech Scene ZA.

As South Africa’s warehousing and logistics sector accelerates digitisation to improve efficiency, a growing blind spot is emerging: many digital rack and inspection systems are not built to operate reliably in real warehousing conditions, and the costs are showing up in the margins, not just operations.

While working with various warehousing clients, Specno specialists have noted a disturbing pattern across warehouse management and inspection platforms: systems that look robust on dashboards actually break down at the point where data is actually captured.

“We’ve become so focused on the potential savings of digitisation that we’ve ignored the colossal cost of when these systems inevitably fail. The silent, creeping expenses of bad data, signal loss, and system downtime are creating a financial black hole in South Africa that, for many, is proving more costly than the analogue inefficiencies they sought to escape,” says Joshua Harvey, Head of Growth at Specno.

With South African online retail projected to surpass R130 billion in 2025, online retail is expected to account for nearly 10% of all retail sales in South Africa. In this high-stakes environment, even a minor system glitch doesn’t just cause a hiccup; it triggers a catastrophic financial chain reaction.

“Warehousing software often assumes perfect connectivity, clean workflows, and low-pressure environments,” says Harvey. “But warehouses are fast-moving, offline-prone environments. If inspection data can’t be captured and synced reliably under those conditions, the result isn’t just operational friction, it’s repeat work, delayed reporting, higher support costs, and margin erosion.”

Many warehouse operators have digitised inspections, racking audits, and corrective actions, but without validating whether those systems can handle offline work, high data volumes, and real-world inspector behaviour at scale. Common failure patterns have included inspection data that appears “saved” but is later lost or only partially synced; inconsistent inspection status across mobile, web, and reporting tools; and platforms that slow down, stall, or require manual workarounds as warehouses or sites scale.

The most visible failure noted by Specno has been downtime: “While many South African executives might budget for occasional maintenance, they are unprepared for the reality that a single hour of downtime is now costing the average industrial business over R724,000. For a typical warehouse or distribution center, the figure is estimated to be between R180,000 and R250,000 per hour” adds Harvey.

What inspection data really represents

“In warehousing and logistics environments, inspection data refers to the information captured by inspectors during physical checks of racking, storage structures, and warehouse infrastructure. Inspectors are typically trained field staff who move aisle by aisle, rack by rack, recording observations, damage, load risks, photos, timestamps, and required corrective actions, often under time pressure and in low-connectivity conditions” says Harvey.

This data forms the backbone of reporting, invoicing support, client assurance, and internal decision-making. When inspection data is incomplete, inconsistent, or unreliable, warehouses may face repeat inspections, delayed sign-off, disputed outcomes, and slower revenue recognition.

Why this becomes a margin and scale problem

Harvey concludes that: “Silent data loss and system performance degradation are particularly damaging because they often go unnoticed until operations grow or commercial pressure increases. What starts as a technical inconvenience can quickly become a problem, especially in multi-site or fast-scaling warehouse environments.”

A system that ‘usually works’ forces people to compensate. That compensation shows up as rework, manual checks, longer inspection cycles, delayed reporting, and higher operational overheads. Over time, that directly impacts margins. 

Specno says warehouse operators serious about scaling profitably should be evaluating whether their current digital inspection systems can stand up to this level of operational reality.

The post Specno specialists warn of digital warehousing risks that are costing local businesses over R250 000 an hour   appeared first on Tech Scene ZA.

“South Africa is not short on ambition when it comes to artificial intelligence. What we are short on is execution,” announces Joshua Harvey, Head of Growth at Specno, South Africa’s leading digital innovation agency, the company responsible for launching South Africa’s very own Innovators Den. 

While global benchmarks show South Africa is around 35–40% behind the United States in AI readiness, enterprise data reveals an even wider gap in execution, with AI implementation rates in South Africa sitting at roughly half the level of the US: “This gap reflects not a lack of will, but differences in skills, data infrastructure, organisational alignment, and the integration of AI into core business strategy” adds Harvey. 

He argues that South Africa’s AI challenge stems from a number of execution barriers, not a single missing piece. These barriers are well documented in recent national and academic analyses:

1. Skills Shortage and Workforce Readiness

Last year, SAP reported findings that South Africa faces a critical shortage of AI-related skills, which threatens to limit the country’s competitiveness and the ability of organisations to realise value from AI technologies. Without coordinated investment in training, certification, and workplace upskilling, this gap will widen rather than close.

2. Organisational and Data Readiness

Successful AI implementation is not simply about acquiring tools; it requires robust organisational infrastructure and data readiness. Research on AI adoption frameworks shows that readiness factors, including data quality, executive leadership support, IT capacity, and available resources, are core determinants of whether AI initiatives succeed or fail.

The study also shows that where organisations lack integrated data systems or strong governance structures, AI pilots often stall and fail to scale. 

3. Low Adoption Despite Acknowledged Value

Even where business leaders recognise the benefits of AI, adoption lags. Studies of South African organisations reveal that many executives understand AI value in theory but are constrained in practice by limited IT maturity, risk aversion, and organisational culture factors that inhibit more transformative adoption.

What the United States is doing Differently

“U.S. firms and institutions have aggressively pushed AI into operational workflows, talent development, and business strategy. Even amid challenges, including debates about deployment scale and workforce impact , American companies maintain strong investments in practical AI applications, cross-functional teams, and data architectures that support industrialisation” says Harvey.

In the U.S., a concerted focus on problem-first deployment, where AI is aligned to cost drivers and operational impediments, has influenced both innovation and productivity. While adoption is still uneven across sectors, the integration of AI into core functions such as supply chains, customer service, and decision support is demonstrably more advanced than in South Africa.

What can South Africa do to catch up?

Harvey believes that we cannot work from an aspirational future state: “We must benchmark honestly against where we are today and commit to concrete shifts in capability and practice.”

AI literacy at executive and board level must improve, but this must be matched with practical implementation skills. From data engineers and machine learning operators to product managers who can translate business needs into technology outcomes.South Africa’s strongest opportunities lie in sectors such as financial services, healthcare, energy, and logistics;  areas where inefficiency is measurable and improvements deliver real value. AI must address tangible, locally relevant problems that matter to the economy and citizens.

Government, Industry, and Academia must Collaborate

“Filling the skills gap and strengthening data ecosystems requires coordinated action across all sectors. National initiatives that support training, certification, and research collaborations can accelerate readiness and ensure South Africa’s workforce is prepared for the demands of AI-driven economic participation. South Africa stands at a pivotal point. The next 12 months will determine whether we remain followers, or whether we narrow the execution gap and build AI systems that are robust, ethical, and commercially viable in our context” concludes Harvey.

Businesses looking to operationalise AI responsibly, pragmatically, and at scale are encouraged to engage with Specno, a local digital innovation agency focused on turning complex technology into viable, production-ready solutions that solve real-world problems.

The post Studies show SA trails the U.S. in AI implementation by 50%: confirmed by SA’s leading digital innovation agency  appeared first on Tech Scene ZA.

South Africa – As global organisations race toward 2026, Specno is issuing a clear warning: businesses that do not rethink how they build digital products will be left behind in what leaders are calling the fast-fashion era of tech.

With AI now enabling rapid development at unprecedented speed, the competitive landscape has fundamentally changed. Speed alone no longer wins; in fact, it increases the risk of launching products that are misaligned, commercially weak, or easily duplicated.

“Sam Altman said it best: we’re entering the fast-fashion era of tech building,” says Joshua Harvey, Head of Growth at Specno. “Anyone can create something quickly today, but very few are creating the right thing. In 2026, product discipline will become the new measure of competitiveness.”

The rise and risk of fast-fashion tech for Africa

Businesses across Africa and the world are falling into the same pattern: building fast, copying trends, skipping validation, and flooding the market with disposable digital tools. The consequences are predictable: high burn rates, missed product–market fit, and a growing graveyard of failed apps.

Harvey adds, “Businesses are shipping features instead of understanding behaviour. They’re building quickly instead of building intentionally. The result is a wave of products that launch with excitement but fade just as fast.”

What does this mean for builders?

As low-effort tools saturate the market, companies are realising that differentiation no longer comes from speed, it comes from strategic clarity. The winners will be the ones who treat product as a craft: selective, evidence-based, and commercially grounded. This shift is driving organisations to seek premium product consulting rather than simple development. 

Specno, a local digital innovation agency, has positioned its Product Strategy practice to meet this need, serving as a partner that ensures businesses build the right product before writing a single line of code.

Specno does this by ensuring a clear, end-to-end product strategy that focuses on real customer validation, strong value propositions, data-driven UX design, precise guidance for engineering teams, and commercialisation support that drives adoption, growth, and long-term scalability.

“We work with leaders who understand that premium products aren’t rushed, they’re meticulously engineered,” Harvey says. “Our goal is simple: eliminate the guesswork, reduce the risk, and help companies build products that matter, last, and perform.”

Are South African businesses ready for 2026?

Specno advises executives to review their product readiness across five critical questions:

1. Do you know exactly who your customer is – and why they’ll choose you?
2. Have you validated behaviour, demand, and willingness to pay?
3. Are decisions guided by evidence or internal assumptions?
4. Would your product survive in a fast-fashion tech market?
5. Do you have an iteration, data, and relevance strategy?

If the answer to any of these is “not fully,” it means there’s room to refine, validate, and set the product up for greater success.

Specno emphasises that the next decade will not be shaped by how fast companies build, but by the clarity, intention, and evidence behind what they choose to build. In an era where anyone can build quickly, the businesses investing in disciplined product thinking will be the ones that stand out, scale, and set the pace for Africa’s digital future.

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A recent MIT report featured in Fortune magazine revealed that ninety-five percent of generative-AI pilot projects are failing, resulting in investors pulling back and misrepresenting this as a failure of the technology itself.

However, the real failure lies in the way organisations are adopting and managing it. AI does not break business; a poor strategy does. The problem is not how AI has failed to deliver but how too many companies have rushed into it without a plan.

“Too many organisations start with a solution and then look for a problem. This is a wholly redundant approach. Instead, it should be the reverse: identifying a hurdle and assessing whether AI can realistically mitigate it. This requires clarity on workflows, data quality, and change-management processes; the same fundamentals that determine success in any complex software project,” says Daniel Novitzkas, Chairman of Specno.

“The MIT study shows that generic, off-the-shelf AI tools may be adequate for individuals but regularly fail in complex business environments. By contrast, bespoke AI tools designed by specialists enjoy a sixty-seven percent success rate, far higher than the thirty-three percent success rate of internally built tools. The lesson is clear: technology must adapt to the business, not the other way around,” Novitzkas adds.

For South African businesses, the imperative is not whether to adopt AI, but how. The country faces slow economic growth, collapsing infrastructure, and intensifying competition from global giants such as Amazon and Walmart. In such an environment, efficiency is not optional but rather essential. AI offers a practical way to do more with less: automate repetitive tasks, improve forecasting accuracy, and enrich customer insights.

Novitzkas clarifies that “caution is naturally healthy, but fear should not invalidate action. AI’s value rarely arrives with fanfare; it appears quietly in shorter service queues, smarter inventory management, and fewer compliance errors; the kinds of improvements that build resilience over time. When leaders see AI as a tool to enhance core processes, the results are tangible: saved time, reduced costs, and accelerated development.”

“Practical examples from technology partners such as Specno demonstrate what deliberate integration can achieve. Using AI in product development and validation, Specno and its clients have cut validation cycles significantly,, while reducing project costs by up to thirty percent. By embedding AI into traditional workflows and automating design, testing, and analysis, companies are delivering faster, more efficiently, and with greater confidence,” Novitzkas continues. 

“It has never been easier for companies to get the right help. The strategic deployment of AI in the early stages of developing a Minimum Viable Product enables a shorter feedback loop, allowing businesses to make critical decisions more quickly. This faster turnaround means more time dedicated to input and iteration, resulting in stronger, more reliable systems that minimise disruption to operations,” Novitzkas describes. 

Still, many businesses treat AI as a shiny add-on rather than embedding it into their core operations. This adoption gap remains one of the biggest barriers to success. Technology cannot compensate for the absence of strategy, governance, or skilled people. Sustainable adoption requires all three: clear direction, capable teams, and thoughtful process design.

“AI is not a magic bullet. It is objectively a tool. When integrated with clarity and purpose, it has the power to transform efficiency, sustainability, and competitiveness. The future is already rewarding those who choose to make it work intelligently,” Novitzkas concludes.

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