Jem, the fintech provider formerly known as SmartWage, has raised $8.4 million in its first major institutional funding round to expand its WhatsApp-based HR platform into a full AI-native workforce management suite. The round was led by global fintech investor Quona Capital, with participation from the University Technology Fund, E4E Africa, and angel investors including former Old Mutual CEO Iain Williamson.
CEO Simon Ellis said AI can act as a "total enhancer" to workplace relationships rather than depersonalising them. The company uses its own internal AI assistant to scan communication systems like Slack and flag when employees need support or when important milestones occur. The system recently caught that Jem's chief technology officer had worked three weekends in a row without management's knowledge, prompting a mental health check-in.
Ellis said the technology is used to "increase the rate at which a manager can make personalised interventions." He acknowledged the model requires employees and employers to accept "a ton of surveillance in that workflow."
Security and legal risk shifts to humans
As AI agents gain access to corporate databases, email accounts and payment systems, the boundary between HR and cybersecurity has dissolved. Anna Collard, head of content strategy and chief information security officer adviser at KnowBe4 Africa, said organisations now manage hybrid workforces where "half of that workforce doesn't have a heartbeat."
The scale of the challenge is significant. Splunk's 2026 report found 96% of information security officers now oversee AI governance and risk across their organisations. The Retail and Hospitality Information Sharing and Analysis Center reported that 71% of security leaders rank AI as their primary point of friction, ahead of ransomware and phishing.
KnowBe4 Africa data shows 64% of South African organisations report their AI use is unapproved or ungoverned, and 38% of local security leaders say AI agents already take autonomous action in workflows. If an employee sets up an AI agent with access to customer data, it becomes an HR, security, legal and Popia compliance issue simultaneously. The legal risk remains with the humans, not the platforms.
This shift is broadening the entry-level pipeline. Employers are looking beyond computer science degrees, ranking analytical thinking, problem-solving, psychology and behavioural economics as essential qualifications for governing how humans and machine agents interact.
Platform dependency risks
Jem uses a three-layer authentication protocol for its WhatsApp-based platform: device-level lock, an application lock, and password protection on individual documents. Ellis disputed concerns about consumer messaging channels, saying "there is this false narrative that WhatsApp is insecure."
But building on third-party channels introduces structural vulnerability. Meta's global pricing adjustments, rolling out on 1 October, are designed to limit message spam and maintain user relevance. While Jem has a direct relationship with Meta as an official solutions provider, shifting platform policies remain a permanent operational variable. AI vendors including Anthropic, OpenAI, Microsoft and Google are similarly adjusting pricing models for tokens and usage.
Organisations also risk undermining technical investments by failing to engage their workforces. Research from the Top Employers Institute shows employees who feel excluded quietly disengage, double-check outputs, or adopt shadow AI tools outside official channels.
Sandra Botha, lead HR auditor at the Top Employers Institute, said "adoption is not automatic." "It has to be designed... Most employees have never been asked how AI is affecting their work, and that gap shows up later in ways that are much harder to fix."
Vodacom offers one working model: it trained employees in HR, finance, legal and compliance to build their own automated solutions using low-code and no-code tools, rather than restricting AI development to isolated specialist teams. HR professionals looking to build similar capabilities can explore an AI Learning Path for HR Managers or broader AI for Human Resources resources.
Why this matters for HR professionals
HR practitioners now carry legal and compliance accountability for AI systems they may not fully control. The shift from top-down AI implementation to citizen developer frameworks requires HR to design adoption into workflows from the start, not after employees have already found shadow tools. The practical starting point: audit which AI agents have access to employee data in your organisation, and confirm who carries the legal risk when those agents act.
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