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Using AI in Business: At What Level Are You Using It?

Everyone is talking about using AI in business. But “using AI” does not mean the same thing for everyone.

For one business owner, it may mean using ChatGPT to write a WhatsApp message. For another, it may mean connecting AI to internal documents. For someone else, it may mean allowing AI agents to follow up with customers, update CRM records, or even build internal software.

So before we ask, “Should SMEs use AI?”, a better question is:

At what level is the SME using AI — and who is still in control?

The higher we go, the more AI moves from being a helper we manually call to becoming a participant inside the business. The benefit increases, but so do the risks around data, cost, customer experience, compliance, and accountability.

Table 1: SME AI Usage Levels

LevelSME AI StageBuzzwordWhat it meansSME exampleHuman roleCost / token exposureRisk / caution
1Free AI useChatGPT, Gemini, Claude, DeepSeekYou manually ask AI and use the answerCaptions, messages, ideas, translationYou ask, read, decideFree or limited free usageLow, but don’t share sensitive data
2Paid AI usePlus / Pro / Advanced AIMore capable AI used manuallyEmails, proposals, reports, Excel help, planningYou ask, read, decideFixed monthly subscription; usage limits may applyLow to moderate
3Multimodal AIMultimodalAI can read text, images, PDFs, screenshots, audio, etc.Invoice reading, product photos, forms, cataloguesYou still trigger AI manuallySubscription or usage limits; file-heavy work may cost moreModerate; wrong interpretation risk
4AI with your business dataRAGAI searches or refers to your own documents/data before answeringPrice lists, SOPs, FAQs, policies, cataloguesYou control what data it can accessToken usage during search and answers; recurring cost possibleData exposure and wrong-answer risk
5AI inside business toolsAI-enabled CRM / ERP / Marketing / Sales toolsAI features built into tools you already useAuto drafts, summaries, lead scoring, invoice remindersYou review AI suggestions inside the toolUsually subscription-based; token cost hidden inside vendor pricingVendor-dependent; data risk; hidden pricing or lock-in risk
6AI automationWorkflow automationAI is connected to repeated workflowsLead follow-up, reminders, report generation, stock alertsYou define rules and monitorToken usage during operations; cost may grow with volumeWorkflow errors, data risk, unplanned operating cost, tool dependency
7AI agentsAgents / Agentic AIAI can take steps on its own: read, decide, act, update, messageAgent follows up leads, updates CRM, prepares reportsHuman supervises and sets boundariesToken usage during operations; cost not yet stabilizedHigh; needs strong controls; data, cost, customer experience, compliance and legal risks

At Levels 1 and 2, AI is mostly helping us think, write, summarize, or plan. At Levels 4 to 7, AI starts touching business data, workflows, customers, tools, and decisions. That is where SMEs need to become more careful.

A simple cost rule is this:

Building with AI may be a one-time cost. Running a business process through AI may become a permanent meter.

If AI is used only while designing or building something, the token cost may stop after development. But if AI is used every day inside operations, token usage becomes a recurring business cost. These costs have not fully stabilized yet.

Table 2: When SMEs Use AI to Build Software or Apps

There is another important category: SMEs using AI to build software, dashboards, apps, portals, or internal tools. This is where terms like AI-assisted coding, agentic coding, vibe coding, and AI-reviewed code become important.

LevelSME AI Software StageBuzzwordWhat it meansSME exampleHuman roleCost / token exposureRisk / caution
8AI-assisted codingAI coding assistant / Copilot / Claude CodeAI helps write parts of the software, but a human designs and understands the systemDeveloper uses AI to build a quotation tool, dashboard, or report module fasterHuman designs, reviews, tests, and owns the codeToken/subscription cost during development; usually no token cost during operations unless AI is embeddedLow to moderate if reviewed properly
9Agentic codingAgentic coding / coding agentsAI reads the codebase, edits files, runs commands, fixes errors, and iterates across stepsAI helps modify an internal order-tracking app or CRM workflow across multiple filesHuman directs, supervises, reviews, and verifiesHigher token usage during development; usually no token cost during operations unless AI is embeddedModerate to high; wrong changes can spread across the system
10Vibe codingVibe coding / prompt-to-app / no-code AI app buildersHuman describes what they want, AI builds something that seems to work, but internals are not deeply understoodOwner builds an app for orders, billing, stock, follow-up, or customer records by prompting AIHuman experiments and accepts what works on screenToken/subscription cost during design/build; operations cost depends on platform and hostingVery high if used for real business without technical review
11AI-generated, human-reviewed systemsAI-generated code with white-box reviewAI writes major parts of the system, but a capable human reviews architecture, code, security, testing, and failure casesSME builds a custom MIS, customer portal, or operations tool with AI support and developer reviewHuman remains clearly accountableToken cost during development; operations cost depends on whether AI is embedded in the appManageable if properly reviewed, tested, and maintained
12AI-generated, AI-reviewed, human-rubber-stamped systemsAI reviewing AIAI writes code, AI reviews it, AI explains why it is fine, and humans approve without deeply understandingBusiness-critical app is built fast, but nobody can clearly explain or maintain itHuman appears accountable but may not be meaningfully in controlToken cost during development and review; operational cost may also continue if AI is embeddedExtremely high; creates hidden technical, business, data, legal, and continuity risks

In software, the main risk is not whether AI helped write the code. The real risk is whether any capable human understands, reviews, tests, maintains, and owns what has been built.

AI can help build business software faster. But if nobody understands the system, the business may become dependent on something it cannot control.

The Core Question for SMEs

AI is useful. It can save time, reduce manual work, improve communication, support decision-making, and help build internal tools faster. But SMEs should not use AI blindly.

Before using AI deeply in business, every SME owner should ask:

  • Am I using AI to improve my thinking, or am I surrendering my thinking to AI?
  • Am I using AI to become more independent, or am I becoming dependent on tools, vendors, subscriptions, token costs, and lock-ins I do not fully understand?
  • Who understands the system?
  • Who checks the output?
  • Who owns the decision if something goes wrong?

AI should help SMEs become smarter, faster, and more capable. It should not quietly take away thinking, independence, data control, or business ownership.

Use AI. But do not surrender your judgment, your data, or your business control.

About the Author

Bhagath Singh Karunakaran is an entrepreneur, systems thinker, and deep-tech practitioner with over two decades of experience across software, IoT, Industry 4.0, and AI-led business transformation. He is the founder of i45G, where he works with SMEs, institutions, and leaders on practical technology adoption, systems thinking, workforce readiness, and AI-enabled business transformation.

Through his writing and consulting, he focuses on helping business owners and decision-makers move beyond hype and adopt technology with clarity, ownership, and measurable value.