AI-First and 40+ AI Terms Every Business Should Know in 2026

To founders and business owners: we at MONA are not writing this to sell services. We just read Stanford AI Index 2026: 88% of organizations worldwide already use AI in at least one department. In Vietnam, 73% of businesses have tried it too (VINASA 2025). But only 6% are really making big money from AI. That gap has a name: AI first. In this article we share everything: the definition of AI first, 40+ AI terms every business must know, MONA's internal case of cutting costs by 60% and raising productivity by 900% since 2026, and a concrete roadmap so we can rise together in the age of automation. This article is a AI roadmap for business leaders is recommended further reading.

What AI first means and why 2026 is the turning point

Before going deeper, we want you to hold on to the core point: AI first is not a marketing slogan. See also how employees react when the boss rolls out AI. It is how the world's leading companies are changing the way they operate.

The term AI first was declared by Sundar Pichai (Google CEO) at Google I/O 2017, marking the shift from “mobile-first” to an “AI first world.” That vision set a 10-year mark. Right in 2026, the leading companies have entered the stage of truly operating AI first.

As of 2026, AI first is the core operating model, not an add-on layer. AI is the “primary actor,” the main character, in the process of creating value. You still matter, in the role of designing, supervising and making the final call. Manual, repetitive work, producing numbers, sending emails, drafting reports and answering tier-1 questions are all done by AI.

Businesses AI first is very different from a business that merely “uses AI.” When something new needs doing, the first question is no longer “who do we hire” but “can AI do it, how far, and which part is for people.” Every process is redesigned around AI's new capabilities.

If you want to go deeper than the basic definition, read What is AI first? A strategy that puts AI first. The article we are writing here focuses on 2026 execution, specifically for Vietnamese businesses.

AI first vs AI enabled, a quick comparison table

Most Vietnamese businesses today are AI enabled, not AI first. The difference lies in depth, not in whether you use ChatGPT. We have put it in the table below so you can check which tier your business is on:

Theo McKinsey in its report The State of AI 2025 (published 11/2025), businesses that embed AI across functions are twice as likely to beat their industry on revenue growth. AI enabled brings local gains. AI first brings gains that compound over time.

The table also explains why 73% of Vietnamese businesses already use AI but only 13.8% deploy it at scale. Most stop at the AI enabledtier and have not reached the AI firsttier. This is not a weakness, it is an opportunity. We are about to point out the next step.

Where Vietnamese businesses stand in the 2026 AI first race

To show you how important AI first is, we share 3 groups of numbers below. None are picked at random, and all have clear sources.

Global numbers 2025-2026

• 88% of organizations use AI in at least 1 business function (Stanford AI Index 2026).
• 72% use GenAI, double the 33% of 2024 (McKinsey State of AI 2025).
• Only 6% are “AI high performers,” attributing more than 5% of EBIT to AI.
• 74% of businesses rank “hallucination” (AI making things up) as the biggest risk.
• Private AI investment in the US in 2025 reached USD 285.9 billion, 23 times China's.
• GenAI is estimated to add USD 2.6 to 4.4 trillion per year to the global economy (McKinsey).

Vietnam numbers, the real picture

• 73% of Vietnamese businesses have adopted AI at some level.
• Only 13.8% deploy AI at scale, most stop at the pilot.
• Only 36.5% have a written AI strategy.
• 46.4% of businesses lack in-house AI skills, the biggest barrier.
• Vietnam Enterprise AI market 2025: USD 161.41 million, projected to reach USD 1.83 billion in 2034 (CAGR 31.01%).
• Top AI supply sectors: IT (31%), finance (22%), education (17%). Top demand sectors: finance (26%), education (23%), manufacturing (21%), healthcare (16%), logistics (15%).

The turning-point year: Vietnam's AI Law takes effect 01/03/2026

The National Assembly passed the Law on Artificial Intelligence on 10/12/2025, effective from 01/03/2026. The law sets 3 risk levels (inspired by the EU AI Act's 4 tiers), requires businesses to set up AI governance and provides an incident reporting portal. At the same time, VINASA launched STAIR Framework, the first AI Readiness self-assessment for Vietnamese businesses. See details in the AI rollout handbook framework for Vietnamese founders.

Five minutes of reading is enough to see this is not a fad, it is a foundational shift. We, founders and MONA alike, are “halfway up the slope.” It is both a risk of falling out of the global race and a chance to learn from those ahead and avoid their mistakes. It is the perfect moment to pick a path AI first now, instead of waiting another 2-3 years.

If you want to look at it by industry first, MONA has a series: AI in banking, AI in healthcare, AI in logistics, AI in education, and the roundup 9 uses of AI in business.

You tried AI and felt it could not do much, and you are not wrong

We guess some of you are thinking by now: “There is so much AI hype online. I tried it, it could barely do anything, and now MONA is jumping in to hype it too?”

We understand that feeling. And we will say it straight: you are not wrong.

Most Vietnamese-language AI content online in 2025-2026 comes from 3 groups:

1. People selling AI courses and ebooks, whose main goal is selling. They hand you copy-paste prompts that make a nice demo and never show you when the AI gets it wrong.
2. Anonymous video channels, TikTok channels running AI content, who pick the clips where AI did well and cut out the parts where it did badly.
3. Self-styled AI “gurus” on Facebook, who need engagement and do not need real operating results for your business.

They DOES NOT do not use AI to run a business. They use AI to make content about AI. You try their way, get no results, feel embarrassed and start doubting yourself. You are right. Their way is surface-level.

There is a quieter pain that is even worse: you ask an employee to research whether “AI can replace your own role,” and the default answer will always be “AI can't do it yet, boss”. We get it, MONA has been there. This is not a bad employee, it is a structural conflict of interest: nobody volunteers that they can be replaced. Klarna in 2024 hit exactly this: customer service said AI could replace them → they rolled it out fully → in 2025 they had to partly reverse it (see the Klarna case below). AI assessments must come from a third party, not from the team being paid for that very position. MONA has written this up in full in 12 months to become an AI first business. MONA has written this up in full in mistakes when rolling out AI in business. MONA has written this up in full in assessing your business's AI readiness.

There is another pain tied to credibility: some of you in leadership try AI yourselves, and every time an employee asks something you open ChatGPT and copy-paste the answer. Your staff see through it right away and lose respect. We understand, because in Vietnamese culture a leader is expected to have “knowledge” and “capital.” But an AI first leader is not a leader who COPY-PASTES AI, but one who KNOWS HOW TO BUILD AI systems so the whole team has answers. Your role is not to “answer questions” but to “build the machine that answers questions automatically.”

So what separates AI that “can't do anything” from AI that is “stronger than a whole department”?

The truth is, you do not need “AI”. You need business automation software.

Look at any task in your business: taking orders, calling customers, reconciling accounting, running payroll, writing reports, after-sales care, screening job candidates. There is one simple question for each: can this be handed to a machine to do on its own?

10 years ago the answer for most tasks was “no, machines don't understand human language, can't see images and can't speak”. Now, in 2026, the answer has flipped:

• Large language models (LLMs) unlock all the work around reading, understanding and writing Vietnamese: replying to customers, summarizing reports, drafting emails, screening CVs, checking contracts.
• Computer vision unlocks work involving images and video: counting customers at the door, checking product defects on the line, reading paper invoices, recognizing license plates.
• Voice / Speech unlocks work involving speech: calling customers in place of staff, taking meeting minutes, converting speech to text and back.

The set of tasks “a machine can do on its own” is now 10 times wider than in 2016. Technically, almost anything you want a machine to do, it can do. But most Vietnamese businesses still haven't put it in place. Seen on its own it still looks confusing, nobody guides them, and they fear trying wrong.

We at MONA chose a different way. We do not hype “general AI.” We go into each specific task in the business, write automation software for it, run it for real and measure it for real. Our next series goes deep on one task at a time: what machines can do, which industries MONA has delivered for, what it costs and what the results are. MONA has written this up in full in Vietnamese voice AI for call center callbots. MONA has written this up in full in why Vietnamese businesses fail at AI. MONA has written this up in full in AI replaces average employees, not the top 10%.

👉 Follow the Business automationsection, a series where MONA shares real experience from our own operation and about 30 close clients. No trend-chasing, no course selling, only what we have done and measured.

We are sharing this long article not to ride a trend. MONA has done this for real, on our own operation and about 30 close clients, at the level of fully automating the work of a whole department. Below are the numbers we measured in the first 5 months of 2026, not “engagement bait” numbers.

MONA, a Vietnamese AI first business since 2026: 60% lower costs, +900% productivity

Before we tell the internal case, we have one direct question for you: what do we really want?

We want to cut costs. We hate bureaucracy most of all. We want less back-and-forth between people and between departments, because those handoff loops are exactly where bureaucracy, delays and mistakes creep in. We want staff to put their energy into creating value, not sitting there copy-pasting, reconciling Excel files and sending reminder emails.

That is exactly why MONA decided to move to AI first from early 2026, not because of a trend, but because we hate bureaucracy just as much as you do. After a 12-month pilot, MONA's leadership officially committed to operating AI first. Here are the numbers we measured in the first 5 months of 2026:

60% lower operating costs on roles converted to AI first

When MONA redesigns processes around AI instead of bolting AI onto old processes, variable costs drop sharply. Here are the specifics:

• Content production: cost down 70%. An SEO article used to need 2 people (a researcher and a writer) for 6 hours. Now an AI Agent does 80% of the article, and a person only edits and verifies in 1 hour.
• Customer Support tier-1: cost down 65%. Chatbot AI MONA holds CSAT above 90% for the 78% of incoming tickets.
• Order reconciliation, internal accounting: cost down 55%. RPA + AI replace 90% of data entry and reconciliation work.
• QA code & review: cost down 50%. An AI Coding Assistant catches 70% of bugs at the dev stage, reducing downstream hotfixes.

In total, across the roles that have been converted to AI first, MONA measured a 60% cost reduction at the end of Q1/2026 compared with the same period in 2025.

+900% productivity from AI Agents replacing manual workflows

Productivity does not mean “9 times faster.” It is a throughput metric, the amount of output produced per person per hour, up 900% on roles converted to AI first. This number comes from 3 sources:

1. AI Agents run 24/7 without rest. A human team works 8 hours a day while an agent runs 24, which is already 3x output on the same task definition.
2. AI Agent parallel: One employee cannot do 10 tasks in parallel, but AI can. MONA runs 50 parallel instances for some workflows.
3. AI Agent + people = a smarter design than the old workflow. People no longer do the repetitive part and put all their energy into creativity and judgment.

Result: with the same team, MONA's Q1/2026 output equals the entire 2024 output combined.

Many roles automated 100%, no human touch needed

By May 2026, MONA had moved these roles to 100% automatic, with people only auditing periodically:

• AI SDR outbound: prospecting, sending emails, qualifying leads and booking demos, all done by agents.
• CSKH tier-1: chatbot + voice agent handle 78% of cases without escalation.
• Order reconciliation, status updates, sending customer confirmations: automation software MONA wrote itself, with modules linked into a closed chain.
• Daily/weekly internal reports: AI pulls numbers from the DB, writes the narrative and sends it to Telegram/Slack.
• Bug ticket triage, priority classification and routing to the right team: handled entirely by agents.
• Onboarding new customers: email sequences + chatbot + documents generated automatically by profile.

This automation does not “cut people.” MONA moves staff into higher-value roles: AI training, prompt engineering, AI governance and senior customer success. We see this as the most decent way to use AI: freeing people from repetitive work, not removing people. MONA has written this up in full in hire more or automate.

The roadmap MONA went through, 4 phases over 18 months

1. Months 0-3 (Q4/2024): Audit AI readiness across the whole organization. Pick the 5 use cases with the fastest ROI.
2. Months 3-6 (Q1/2025): Trial 5 specific tasks with large language models (LLMs). MONA wrote its own internal automation software (no drag-and-drop tools) and built a standard prompt framework for the whole team.
3. Months 6-12 (Q2-Q3/2025): Expand to AI Agents + internal RAG. Set up AI governance ahead of Vietnam's upcoming AI Law.
4. Months 12-18 (Q4/2025-Q1/2026): Redesign the org chart. Measure EBIT-from-AI. Declare AI first operations official from early 2026.

Your business can absolutely move faster, because you have MONA and the international cases as references. We are ready to share the detailed playbook with anyone who needs it.

3 international AI first case studies you should know: Shopify, JPMorgan, Klarna

Shopify, the “Reflexive AI Usage” model

In April 2025, CEO Tobi Lütke sent an internal memo: “Before asking for headcount, teams must prove AI cannot do the job.” AI usage became a KPI in performance reviews. Eight months later, US companies copied it, and the share of job postings requiring AI skills rose from 5% to 9% in a year. This is a model of AI first enforcement through HR policy, not just a slogan.

JPMorgan Chase, AI-Connected Enterprise

JPMorgan rolled out to LLM Suite for more than 200,000 employees for daily use. By 2026 it had over 600 use cases in production, delivering USD 1.5 to 2 billion in value per year. CEO Jamie Dimon said openly: they spend USD 2 billion a year on AI and save about USD 2 billion. Investment bankers automate 40% of research; traders cut research time by 83%. This is a AI first corporate-style rollout, scaling from pilot to the whole organization in 18 months.

Klarna, the reverse lesson on human-in-the-loop

In 2023-2024 Klarna replaced 700 customer service staff with AI, claiming USD 40 million in annual savings. In early 2025 it partly reversed course because CSAT dropped and AI could not handle complex edge cases. CEO Sebastian Siemiatkowski admitted: “Cost seems to have been a too predominant evaluation factor.” See details in a practical Vietnam AI First roadmap.

The key lesson for you: AI first does not mean replacing people 1:1. You need a mechanism for Human-in-the-loop, with people approving at high-risk points. MONA learned this lesson from the pilot, so every workflow has an “AI confidence threshold,” and below the threshold it hands over to staff automatically. We share this experience so you can avoid the pitfall Klarna already fell into.

40+ AI terms every business must know in 2026

This is the part to bookmark. We split it into 8 clusters for easy lookup. Each term has the English name, the Vietnamese name, a plain explanation and a usage example, so when your tech team reports, you follow right away and do not get “lost in jargon.”

Cluster A, AI foundations

Cluster B, AI models

A few specific AI products worth remembering: ChatGPT, Claude AI, DeepSeek, Perplexity AI, Manus AI, Midjourney, Leonardo AI, SearchGPT.

Cluster C, Core techniques

Cluster D, Agentic AI (the hottest cluster of 2026)

Cluster E, Workflow & Automation

Cluster F, Infra & Ops

Cluster G, Governance & Compliance

Cluster H, Vertical hot 2026

A total of 40+ AI terms that every business must know in 2026. Print it or bookmark it to look up when needed. We update this list regularly because the AI cluster changes faster than the stock market.

A 6-step roadmap to move a Vietnamese business to AI first in 2026

From MONA's experience and VINASA's STAIR model, here are the 6 steps we recommend for you. They are simple, and you can start this week:

1. Audit your current AI maturity. Score yourself on 5 axes: strategy, data, talent, governance, technology. Takes 2-3 weeks.
2. Pick 3 use cases with fast ROI. Prioritize work that has enough data, measurable results and no legal exposure. Tier-1 customer support, content production and accounting reconciliation usually win fast.
3. Build AI Governance. Meet the Vietnam AI Law, effective 01/03/2026. Define the 3 risk levels, who approves, how long logs are kept, and an internal incident reporting portal.
4. Run a 90-day pilot. One small squad (PM + developer + domain expert) per use case. Do not drop AI into the old process; redesign the process around AI.
5. Scale and train the whole organization. Once the pilot has clear numbers, expand to other departments. Every employee learns prompt engineering and basic AI literacy.
6. Measure and iterate every quarter. Track AI leverage ratio, EBIT from AI, customer NPS and time-to-value. Cut use cases that show no ROI after 6 months.

By completing all 6 steps, a Vietnamese SME with 100-200 staff can reach the AI first state in 12-18 months. You can go faster if you choose the right partner. What matters most is to start; we do not have another 2-3 years to hesitate while competitors are already running.

MONA walks with you on the AI first road

Thank you for reading this far. We shared such a long article not to pitch a service, but because we truly want you to see the opportunity that is opening up. If the roadmap above fits you, the MONA ecosystem can support you in 3 main areas:

• Mona.Software, custom software with built-in AI: custom CRM/ERP/HRM with an AI agent for each module, and packaged products (EduCenter, JMS, LMS, SkillHub) that already integrate GenAI.
• Mona.Media, services for AI Marketing, AI SEO, design AI-ready websites, marketing automation. Helping your brand gain visibility on Google as well as on ChatGPT, Perplexity and AI Overviews.
• Mona.Host, GPU VPS and AI inference infrastructure that meets a company's internal AI workloads, with no need to send data abroad.

In addition, the MONA ecosystem also includes Mona.Academy, a business management SaaS suite (expense ledger, team budgets, agent management) with built-in AI workflows, and SkillHub, an internal training platform that helps you upskill AI literacy across the whole team. For individuals who want to learn AI properly, Khánh Hùng Academy (40,000+ students) is the training sub-brand led directly by MONA's founder.

Contact us through the MONA website or Zalo OA and we will audit your AI readiness and propose the 3 fastest-ROI use cases for your business. Consulting is free, because at MONA, your success is our success.

Conclusion: Let's rise together in the AI first era

The age of automation waits for no one. But it does not leave behind anyone who dares to step forward. Having read this far, we believe you are a business owner who looks far ahead and acts.

AI first is not a destination, it is a new way of operating. 88% of the world is already on the road. 73% of Vietnamese businesses have tried it. The question is no longer “should we use AI or not”, but “how fast do we rise together in the race AI first ?”.

MONA has been through the pilot stage and is now cutting costs by 60% and raising productivity by 900%. We are ready to share everything we have learned, so you do not stumble on the stretches of road we have already walked. You and MONA, rising together in the era of AI first this URL.