Blog
AI agents in business, by topic
90 articles organized as a topical cluster: from fundamentals to buying decisions, through implementation, architecture and governance.
Start with the guides
The pillar AI Agents for Business What AI agents for business are, the work they already execute, the three adoption levels, and how to decide between buying, building or contracting. 16 articles Agents by Business Function AI agents in operations AI agents in operations, separated from demo-ware: the difference between an agent that answers and one that operates with permissions and traceability. 13 articles Industries Agentic AI by Industry Agentic AI by industry: the adoption pattern is the same everywhere; what changes is which processes weigh, which systems rule and which rules apply. 6 articles Implementation How to Implement AI Agents in Your Company, Phase by Phase How to implement AI agents, phase by phase: choose the process, map it, integrate, deploy with permissions, evaluate and operate under supervision. 12 articles Architecture & Technology AI Agent Architecture AI agent architecture piece by piece: model, orchestration, tools, memory, evaluation, observability and human controls. 13 articles Governance & Risk AI agent governance AI agent governance by design: permissions, action limits, traceability, human review and controls adapted to the operation. 8 articles Buying Decisions Buy AI, build it or contract the outcome Buy, build or contract AI as a service: choose according to the operation, available team and responsibility you want to retain. 13 articles Vision & Strategy An AI-first organization is not a company that uses AI tools What an AI-first organization is: three levels, from tools to operating model, and why most companies stop at the first one. 9 articles
Agentic AI Fundamentals
15 articles · the guide →
What Is an AI Agent: Definition, Components and What It Is Not What is an AI agent, its five components (model, instructions, tools, memory and controls) and what an AI agent is not: neither a chat nor a script. Agentic AI Meaning: What It Is and How to Tell It From the Hype Agentic AI meaning explained: what it adds over generative AI, and the observable criteria to tell real agency from a chatbot with a marketing budget. Agentic AI vs AI Agents: What Each Term Means and When It Matters Agentic AI vs AI agents: one is the paradigm, the other the concrete systems. When the distinction decides a purchase, and when it is just vocabulary. Agentic AI vs Generative AI: How They Differ and What Changes for Your Company Agentic AI vs generative AI: one produces content on demand, the other pursues goals by acting. What changes for a company and why the jump is engineering. How Do AI Agents Work? How AI agents work under the hood: the perceive, reason, act and observe loop, how they use tools, and why they sometimes get it wrong. Autonomous AI Agents: How Much Autonomy to Actually Grant What autonomous AI agents are, the real grades of autonomy, and how to calibrate how much to grant each decision based on its risk. Types of AI Agents: The Taxonomy That Actually Helps a Business The types of AI agents that matter to a company, classified by function, by grade of autonomy, and by where they live, with when each one fits. AI Agents Examples in Real Life: Work They Already Execute AI agents examples in real life from operations: what each one receives, decides, executes and when it escalates, described as market scenarios. Multi-Agent Systems: What They Are and When They Pay Off What multi-agent systems are, why one agent sometimes isn't enough, how several coordinate, and which business problems justify the complexity. Agentic Workflows: What They Are and Why They Win in Operations What agentic workflows are, the middle ground between a rigid flow and a loose agent, and why they usually win in operations on predictability. RPA vs AI Agents: What Each Automates and When to Migrate RPA vs AI agents: what each automates well, where RPA breaks, what agents add, and why agentic process automation means the two will coexist, not compete. Copilot or AI Agent: How to Decide Which You Need Copilot vs AI agent: the copilot speeds up your people, the agent does the work. What changes in accountability, return and vendor dependence. Chatbot or AI Agent: How to Tell Them Apart Before You Buy Chatbot vs AI agent: the chatbot converses, the agent resolves the case. How to spot whether you are being sold a real agent or a rebranded chatbot. How to Build an AI Agent: The Pieces You Have to Construct How to build an AI agent: the pieces you have to construct, why the prototype is easy and the reliable system is not, and when not to build it yourself. Agentic AI Glossary: The Vocabulary You Need in a Meeting Agentic AI glossary: agent, tool use, harness, skill, evals, MCP, RAG and more, defined clearly for executives making decisions about agents.
Agents by Business Function
12 articles · the guide →
Enterprise AI Agents Use Cases: The Catalog by Business Function Enterprise AI agents use cases by function: finance, customer service, logistics, procurement, HR, sales, and how to choose the first one. AI in Finance Operations: What the Agent Executes and What the Controller Keeps AI in finance operations: reconciliation, close, collections, expense control and reporting. What the agent executes and what stays with the team. AI Invoice Processing: The Process Invoice by Invoice, From OCR to Posting AI invoice processing: receipt, data extraction, two-way and three-way matching, discrepancies, approvals and posting. Where classic OCR falls short. AI customer service agents: from answering to resolving the case AI customer service agents that resolve the case in your systems instead of just answering, how to design escalation, and what to measure. AI in logistics and supply chain: the order end to end with agents AI in logistics and supply chain: how an agent tracks orders across carriers, spots deadline breaks early, and handles incidents within rules. AI in HR operations: what agents handle and where a person decides AI in HR operations: which administrative back office an agent can run and the red line of decisions about people, a high-risk regulated area. AI in Procurement: What an Agent Automates and What the Buyer Decides AI in procurement: the admin work an agent runs from order to receipt, offer matching, renewals and price variances, and what the buyer still decides. AI Agents for Sales: the Admin Work They Remove, the Selling They Don't AI agents for sales handle lead qualification, proposals, renewals and CRM hygiene. What the agent automates and what selling stays human. AI Back Office Automation: How to Start and Scale, Step by Step AI back office automation: how to pick the process, the receive-extract-validate-record-escalate pattern, and how to start with one and grow. Order to Cash AI Automation: The Cycle From Order to Payment Order to cash AI automation with agents: order, confirmation, delivery, invoice and collection as one continuous operation, not four departments. Intelligent Document Processing AI: From OCR to Judgment Intelligent document processing AI with agents: extracting invoices and delivery notes, validating against systems, and designing the confidence threshold. AI Agents for Internal Support: Resolve, Don't Open Tickets AI agents for internal support and helpdesk that resolve level one for real (reset, provision, action requests) versus the portal that only opens tickets.
Industries
5 articles · the guide →
AI Agents in Manufacturing: From the Order to Production, No Handoffs AI agents in manufacturing handle production orders, sourcing, quality documentation and plant-office coordination, not real-time machine control. AI Agents in Distribution and Retail: From Order to Delivery, Exceptions Governed AI agents in distribution and retail: multichannel orders, delivery incidents, inventory sync and customer comms in thin-margin businesses. AI Agents in B2B Services: From Contract to Invoice Without Burning Senior Hours How AI agents in B2B services work: which part of the contract-to-cash cycle an agent runs, and what stays the service itself. AI Agents in Media: Run the Process, Don't Mass-Produce Content How AI agents in media work: which editorial operations an agent runs, and why mass-producing content destroys brands. AI Agents for Mid-Market Companies: Better Positioned Than They Think AI agents for mid-market companies of 10 to 500M: why the mid-market is better positioned for agents and which of the three paths fits this size.
Implementation
11 articles · the guide →
Prepare your company for AI agents: processes, data and ownership How to prepare your company for AI agents: processes written down, data made reachable, an authorized owner and the first 90 days. Why do enterprise AI pilots fail? Why enterprise AI pilots fail: a category error in what was bought, pilots without an owner, clean-data demos, and success defined as a demo. How to Take an AI Pilot to Production How to take an AI pilot to production: the four structural differences between demo and operation and the concrete path to cross the jump. How to Choose and Map Which Processes to Automate with AI Which processes to automate with AI: the criteria for choosing a good candidate and how to map a process into inputs, rules, exceptions and outcome. What Data Does an AI Agent Actually Need? The data requirements for AI agents aren't a two-year project: what an agent really needs and what you can safely leave for later. How to Integrate AI Agents With Your ERP, Step by Step AI agents ERP integration done right: read before write, permissions per operation, idempotency, and what to do when the ERP has no API. How to Handle Exceptions and Human Escalation With AI Agents Exception handling and human escalation with AI agents: what an exception is, how to categorise them, and how they become rules over time. How Long Does It Take to Deploy AI Agents? How long to deploy AI agents is not a catalog number: it depends on five factors. I explain them and share the range I have seen in real deployments. Change Management for AI Adoption: What Changes for People When Agents Do the Work Change management for AI adoption: what changes for people when agents execute the work, and why imposing it breeds quiet sabotage. AI Implementation Mistakes: A Catalog and How to Correct Them The AI implementation mistakes I see repeat, each with its mechanism and its correction, from starting with tech to automating a broken process. Can You Adopt AI Without a Technical Team? You can adopt AI without a technical team if you don't take on the technical cycle: the three paths and what each demands of you.
Architecture & Technology
12 articles · the guide →
AI Agent Orchestration: What It Is and How It Works in an Operation What AI agent orchestration is: distributing work, sequencing steps, handling failures and retries, and deciding when a person steps in. AI Agent Orchestration Patterns: When to Use Each One and Its Risk A catalogue of AI agent orchestration patterns with when to use each and the risk it takes on: pipeline, parallelization, supervisor, checker. MCP (Model Context Protocol): What It Is and Why It Matters for a Company MCP model context protocol explained: the open standard that connects AI agents to your systems and data without custom integrations for every case. Enterprise RAG: Why the Hard Part Is Not the Pattern, It's the Corpus Enterprise RAG explained: what retrieval-augmented generation is and why at company scale the hard part is the corpus, not the pattern. AI Agent Evaluation: How to Measure If an Agent Does Its Job Well AI agent evaluation metrics: test cases with known answers, per-task measures and continuous evaluation that separate a demo from a reliable system. AI Agent Observability: Seeing What the System Does While It Runs AI agent observability: per-case traces, operational metrics and degradation alerts to know what a system of agents is doing while it operates. Human in the Loop vs Human on the Loop: Choosing the Supervision Level Human in the loop vs human on the loop: the three modes of human oversight for AI agents and how to choose the right one by type of decision. AI Agent Memory and Context: What an Agent Remembers and What It Doesn't AI agent memory and context: context window vs persistent memory, how to design what an agent should remember, and the risks involved. Choosing the Best LLM for Business Tasks: An Evaluation Method The best LLM for business tasks is chosen per task by evaluating quality, cost, latency and risk, not by brand. The method I use, without vendor lock-in. LLMs for Business: What Your Options Are and How Each Fits LLMs for business: the three model categories, the fit criteria of data, cost, latency and compliance, and why there is no single best model. No-Code Automation vs Custom AI Agents: How to Decide No-code automation vs custom AI agents: what visual automation solves well, where it breaks, and how to decide by exceptions, evaluation and scale. On-Premise vs Cloud AI Agents: How to Decide On-premise vs cloud AI agents: what running AI locally really means, the trade-offs of control, cost and model quality, and the usual hybrids.
Governance & Risk
7 articles · the guide →
AI Agent Security Risks: What Is New and How Each One Is Defended AI agent security risks explained: prompt injection, exfiltration through tools, excessive permissions and the context supply chain, each with its defense. AI Risks for Business: Which Ones Are Real and How to Govern Them AI risks for business with agents: silent error, vendor lock-in, data leakage, compliance and decay, and how to govern each. AI Agent Permissions and Controls: How to Design Them Step by Step How to design AI agent permissions and controls: read, write and forbidden access, spend and action limits, human approvals, and revocation. The EU AI Act and AI Agents: What It Means When You Deploy Them EU AI Act compliance for AI agents in internal operations: the risk-tiered approach, transparency and documentation duties, and who is responsible. AI Agents and Data Privacy: How GDPR Applies to Them AI agents, GDPR and data privacy: minimization, legal basis, the processor role, and data in prompts, traces and subject rights. How to Audit an AI Agent's Decisions Auditing AI agent decisions: what the trace must record, how to reconstruct a case, how review works by sampling, and what an auditor will ask you for. Shadow AI in the Enterprise: How to Surface Uncontrolled AI Use Shadow AI: what it is, why banning it fails, and how to surface employees' AI use and turn it into a governed capability instead of a hidden risk.
Buying Decisions
12 articles · the guide →
In-house team, consultancy or forward-deployed engineers: how to decide In-house team, consultancy or forward-deployed engineers: who maintains the AI, owns the operation and fits each delivery model. How to measure the ROI of AI in operations AI operations ROI measured as cost per operated process: where agents pay off in high-volume back-office work and why pilot numbers do not transfer. Forward-deployed engineer: what it is and what it does on a real deployment Forward deployed engineer meaning: where the role comes from and what it does on a deployment, connecting systems, encoding rules and setting controls. Vendor FDE vs independent FDE: how to decide who you work with Vendor FDE vs independent FDE: the same title is not the same mandate. What each one deploys, what it optimises and what happens when the model changes. Service as software: what it is and how it differs from SaaS Service as software vs SaaS: the software becomes the workforce that does the work. How it differs from SaaS, BPO and consulting. AI Managed Services: What They Are and When to Contract Them What AI managed services are, how a managed AI operation differs from BPO and IT MSP, what the contract must say, and when it beats building in-house. How to Choose an AI Agent Provider: Criteria You Can Verify How to choose an AI agent provider on criteria you can verify: evaluations, traceability, permissions, portability and a clean exit, plus the red flags. AI Agents Implementation Cost: The Structure Behind the Number AI agents implementation cost has a structure, not a single figure: the real cost lines, what moves each one, and the hidden costs no demo shows you. AI Automation Agency vs Managed Operation: How to Decide An AI automation agency ships flows and leaves; a managed operation answers for the outcome. When each one is enough and how to choose without regret. AI Center of Excellence: Do You Need One, or Is It Theater? What an AI center of excellence is, when it makes sense and when it is organizational theater that delays. Alternatives for the mid-sized company. AI Consulting Firms: How to Choose One and What to Ask First A map of AI consulting firms by what each type delivers, the questions to ask before contracting one, and the smoke signals to walk away from. ChatGPT for Business: What It Solves and Where It Falls Short What a ChatGPT for business plan really solves, what drives its price, and where it falls short against agents that execute processes end to end.
Vision & Strategy
8 articles · the guide →
Agentic product development: what changes when agents build the software Agentic product development explained by a practicing CPTO: cycle time, lower adaptation cost and where human judgment concentrates. The operating model as code: executable rules and exceptions Operating model as code: your processes, rules and exceptions codified and executed by agents, why it must be custom, and what the first mover gains. Digital Workforce: What It Is and How It Works Alongside Your People What a digital workforce is: AI agents that execute work next to your human staff, how it is organized, and how it differs from managing people. AI Transformation Playbook: Start With One Operation, Not a Program An AI transformation playbook without theater: start with one operation with a measurable result, not a three-year program. The sequence that works. How to Write an AI Strategy for Executives in Two Pages An AI strategy for executives that fits in two pages and can be executed: the decisions it must contain, what to cut, and the order to decide them in. AI agents and the future of work: what already changes in operations AI agents and the future of work: which roles are shifting today, what capabilities to build, and what nobody can predict yet. How to run an AI maturity assessment: a 5-dimension self-check An AI maturity assessment you can run yourself: 5 observable dimensions, 3 levels each in verifiable behaviors, and which level each ambition demands. The AI operating model: who owns what when agents do the work How the AI operating model changes: who owns process, result, system and data, where controls live, and how the org chart gets redrawn around processes.