Everyone is investing in agentic AI to improve customer experience. Chatbots, virtual assistants, predictive campaigns – the ambition is genuine. So why does the experience still feel fragmented? The answer isn’t the AI. It’s what the AI has to work with. Most enterprise teams operate across a patchwork of platforms: CRM, CDP, contact centre software, […]
Agentic AI Customer Experience: Why Infrastructure Matters Read More »
Kore.ai launched its Artemis platform in May 2026 with a ground-up redesign of how enterprises build and govern AI agents. At the centre of that redesign is Agent Blueprint Language (ABL), a compiled, declarative language that standardises how agents are defined, validated, and controlled before they ever reach production. The problem it solves Most organisations
Kore.ai Artemis: Why Agent Blueprint Language Changes Enterprise AI Read More »
Ivanti’s 2026 AI Maturity Report surveyed 3,900 employees across six countries and landed on a finding that should give every IT leader pause: the gap between how fast organisations are deploying AI and how well they are governing it is widening, not closing. More than half of organisations (56%) are now deploying AI broadly across
AI Is Scaling in IT. Governance Is Not Keeping Up. Read More »
The global conversation around agentic AI in ITSM has shifted. It’s no longer about whether AI belongs in the service desk. It’s about whether your organisation can move from AI-assisted to AI-autonomous before the gap between early movers and everyone else becomes structural. Gartner’s numbers are stark. By 2029, 70% of enterprises will deploy agentic
Agentic AI in ITSM: What South African IT Leaders Need to Know Read More »
The AI agent build vs buy enterprise debate is one that most organisations are not having clearly enough – and it is costing them. Teams spend months building agent infrastructure from scratch, when that time should be going toward the workflows and domain logic that actually differentiate their business. There is a trap that enterprise
Build vs Buy AI Agents: Why South African Enterprises Are Building the Wrong Thing Read More »
Agentic AI for IT service management Key Takeaways AI agents differ from endpoint agents (which collect device data) and automation bots (which execute workflows) by serving as an intelligent orchestration layer that understands natural language, reasons across context and coordinates existing automation. Successful agentic AI for IT requires: clean and current knowledge bases, real-time context
Agentic AI for IT Service Management: Getting Agents Right Read More »
Why conversational AI is now an integration problem, not just a chatbot project Conversational AI integration in 2026 is no longer just about deploying a chatbot. A true conversational AI integration guide needs to go beyond responses and focus on how AI connects to your systems, executes workflows, and delivers measurable business outcomes. For many
AI for Service Delivers Business Value Across HR Operations AI for service in HR operations is helping global organisations manage growing employee support demands without increasing headcount. By embedding AI into workflows, Deutsche Bank has automated routine queries, improved service consistency, and gained insight into support trends – all while controlling costs. This use case
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AI for Service Is Reshaping Customer Operations at Scale AI for Service in global banking, powered by platforms like Kore.ai, is increasingly becoming essential for managing complex, high-volume customer environments. As customer expectations rise and interaction channels multiply, financial institutions require platforms capable of handling scale, precision, and multilingual complexity simultaneously. A global example from
AI for Service in Global Banking: A Citibank Use Case Read More »
Global Lessons from Morgan Stanley Wealth Management AI for Work – From Concept to Competitive Advantage Adaptive AI orchestration in financial services is no longer theoretical. Leading institutions are embedding AI directly into employee workflows to improve productivity and unlock institutional knowledge. At the same time, financial services organisations are under increasing pressure to scale
Adaptive AI Orchestration in Financial Services: A Global Use Case Read More »
