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June 22, 2026 22. junij 2026 M-AI d.o.o 7 min read 7 min branja

How to Choose an AI Agency: Red Flags Checklist Kako izbrati AI agencijo: kontrolni seznam

How to choose an AI agency comes down to one practical question: can they turn AI from an impressive demo into a measurable business result in your environment, with your data, constraints, and goals? The right partner will talk less about hype and more about use cases, integration, governance, adoption, and ROI. The wrong one will sell you flashy prototypes, vague promises, and generic slide decks.

That distinction matters more than ever. AI budgets are growing, but so is scrutiny. According to McKinsey, 65% of organizations report regularly using generative AI in at least one business function, nearly double the share from the previous survey McKinsey, The state of AI in early 2024. At the same time, Gartner has predicted that at least 30% of generative AI projects will be abandoned after proof of concept by the end of 2025 due to poor data quality, inadequate risk controls, escalating costs, or unclear business value Gartner, 2024 press release on generative AI project failure rates. In other words: the market has moved past experimentation, and choosing the wrong AI agency is now expensive.

For companies evaluating partners, the goal is not simply to find a vendor that can build with large language models. It is to find a team that understands operations, product thinking, data quality, system architecture, compliance, and change management. If you are comparing providers for AI strategy, AI automation, custom assistants, or AI-powered software development, this red flags checklist will help you make a smarter decision.

Why choosing the right AI agency matters more than the demo

A polished demo can hide weak delivery capability. In fact, many AI agencies can show a chatbot, workflow, or dashboard that looks convincing in a controlled environment. What matters is whether that solution still performs when connected to your actual documents, ERP, CRM, support inboxes, product catalog, or internal processes.

That is why choosing an AI agency should start with implementation reality, not visual polish. A good partner will explain what happens after the demo: how data is prepared, how success is measured, how hallucinations are mitigated, how users are trained, how systems are integrated, and how security is handled. They will also help you avoid overbuilding, because not every problem needs a custom AI stack.

IBM’s 2024 Global AI Adoption Index found that 42% of enterprise-scale organizations are actively deploying AI, while another 40% are exploring or experimenting with it IBM, Global AI Adoption Index 2024. As adoption rises, buyers need partners who can move from concept to production responsibly. That often means beginning with one high-value workflow, proving ROI, and scaling from there.

“The biggest mistake companies make with AI is not underestimating the technology—it’s overestimating how ready their data, processes, and teams are for it.”

This is where a capable implementation partner stands out. Rather than pushing a one-size-fits-all solution, they assess your current state, identify automation bottlenecks, and propose a roadmap that matches business maturity. For example, a strong firm may start with document processing, AI search, internal assistants, or support automation before expanding into more advanced orchestration or productized AI features.

If you are evaluating agencies, look for evidence that they can work across strategy and execution. At M-AI, for example, that means not just building AI systems but aligning them with real operational outcomes, whether through automation, custom AI solutions, or vertical use cases like solutions showcased on FURS and AI-powered commerce experiences such as Shelfze.

7 red flags that show an AI agency may lack real expertise

1. They lead with tools, not business outcomes

If the first conversation is dominated by model names, frameworks, and trend buzzwords, be careful. Strong agencies begin by asking what needs to improve: revenue, speed, cost, customer experience, compliance, or internal efficiency. Tools matter, but they are downstream of the business problem.

A weak agency may say, “We can build you a GPT-powered assistant.” A strong one will say, “We see three places where AI can reduce manual work by 40% and improve response times within 90 days.” That difference is critical.

2. They cannot explain how they handle your data

Any AI partner working with enterprise information should be able to discuss data access, storage, model routing, retention, permissions, security, and regulatory concerns in plain language. If they avoid specifics, that is a major red flag.

Deloitte research has consistently shown that trust, governance, and risk management are major barriers to AI scaling Deloitte, State of Generative AI in the Enterprise, 2024. An agency that cannot talk confidently about governance is not ready for serious work.

3. Their case studies are vague or unverifiable

“We helped a client transform operations with AI” is not a case study. Real case studies include a business context, scope, implementation approach, timeline, constraints, and measurable outcome. Even when client names are confidential, credible agencies can still describe what was solved and what changed.

Look for details like processing time reduced, conversion rate improved, ticket volume automated, search quality increased, or manual work eliminated. If everything sounds impressive but nothing is measurable, treat that as a warning.

4. They promise full autonomy too early

Be skeptical of any agency that suggests AI will immediately replace teams, run critical workflows unattended, or solve accuracy problems without human oversight. Responsible AI implementation usually starts with human-in-the-loop workflows, monitored outputs, and careful rollout.

Early overpromising often leads to failed deployment, internal distrust, and wasted budget. A mature agency sets realistic expectations about reliability, training data quality, and ongoing tuning.

5. They ignore integration complexity

Most business value from AI comes from fitting into existing systems, not operating in isolation. If an agency shows you a beautiful standalone demo but cannot explain how it connects with your website, CRM, ERP, helpdesk, document storage, or e-commerce stack, they may be stronger in prototyping than delivery.

Integration is often where projects succeed or fail. The best agencies talk openly about APIs, middleware, access control, deployment options, and fallback logic.

6. They have no plan for adoption inside your company

Even strong AI systems fail when nobody uses them. If an agency does not discuss onboarding, internal champions, user workflows, training, and feedback loops, they are ignoring a key part of implementation.

PwC has noted in multiple AI studies that business value comes not just from the technology itself but from redesigning how work gets done around it PwC, Sizing the prize / Responsible AI and enterprise adoption research. In practice, that means the agency should care about how your people will actually use the solution.

7. They cannot define success for the first 90 days

Experienced AI partners know that momentum matters. They should be able to tell you what happens in discovery, what gets validated, what gets built first, what metrics will be tracked, and what decision points will be used to continue, adjust, or scale.

If they jump straight into a long-term retainer or broad transformation promise without a milestone-based plan, that is a red flag. Good agencies make progress visible early.

“People worry that computers will get too smart and take over the world, but the real problem is that they’re too stupid and they’ve already taken over the world.” — Pedro Domingos

This quote captures an important truth for buyers: the challenge is rarely whether AI is magical enough. It is whether the partner is disciplined enough to make it useful, accurate, and operationally safe.

Questions to ask before hiring an AI agency

If you want to know how to choose an AI agency with confidence, ask questions that force specificity. The best agencies welcome this. Weak ones deflect.

Questions about business fit

These questions show whether the agency understands prioritization. You want a partner that can identify quick wins without losing sight of long-term architecture.

Questions about delivery capability

This helps you separate real operators from presentation teams. It also reveals whether senior people disappear after the sales process.

Questions about technical and security maturity

A serious AI agency should answer without hand-waving. They should be comfortable discussing retrieval systems, validation layers, model evaluation, monitoring, and governance.

Questions about collaboration and change management

Good AI delivery is collaborative. If an agency acts like success depends only on their technical build, they are likely underestimating the organizational side of implementation.

What a strong AI partner should deliver in the first 90 days

The first 90 days should create clarity, traction, and evidence. You do not necessarily need a giant finished platform in that time. You do need proof that the agency understands your business, can execute in your environment, and is moving toward measurable value.

Days 1-30: Discovery, prioritization, and feasibility

In the first month, a strong AI partner should map your workflows, identify data sources, define constraints, and shortlist the most promising use cases. This phase should include stakeholder interviews, technical review, risk assessment, and baseline metrics.

Expected outputs might include:

This is where agencies like M-AI can add disproportionate value: by narrowing the field to opportunities that are both technically feasible and commercially meaningful, rather than chasing generic AI ideas.

Days 31-60: Pilot or prototype built around a real workflow

By the second month, you should see a working pilot tied to an actual operational process. That could be an internal knowledge assistant, automated document workflow, customer support co-pilot, AI search layer, recommendation engine, or task automation flow.

The key is that it should use real or representative data and reflect real user behavior. This is not the stage for vanity prototypes. It is the stage for proving utility, constraints, and performance.

A good partner will also establish evaluation criteria. For example:

Days 61-90: Validation, iteration, and scale decision

In the third month, the agency should iterate based on feedback, improve reliability, document results, and help you decide whether to scale, refine, or stop. This phase is where discipline matters. Not every pilot should become a full rollout, and a trustworthy partner will say so when needed.

By day 90, you should ideally have:

If the agency cannot produce that level of clarity, it is a sign they may be improvising rather than executing from a mature process.

Final checklist: how to choose an AI agency without wasting budget

To choose well, look beyond the demo and score each agency on five dimensions: business understanding, delivery evidence, technical maturity, security/governance readiness, and ability to drive adoption. The best partner is not necessarily the one with the most dramatic claims. It is the one most likely to deliver a useful, trustworthy system in your real business context.

As you compare options, ask yourself:

If the answer is yes, you may have found a real AI partner. If not, keep looking. In a market crowded with demos, credibility comes from execution.

Ready to evaluate your AI opportunity?

If you are exploring AI automation, custom AI products, internal assistants, or workflow optimization, talk to M-AI. We help companies identify high-impact AI use cases, validate them quickly, and build solutions that fit real business operations. Whether you need strategic guidance, implementation support, or a focused pilot, our team can help you move from curiosity to measurable value.

Get in touch here: https://m-ai.info/#contact

Kratek odgovor: pravo AI agencijo izberete tako, da ne kupite najbolj bleščečega demota, ampak partnerja, ki zna povezati poslovni cilj, podatke, procese, varnost in merljive rezultate. Če agencija ne zna jasno razložiti, kako bo v 90 dneh dokazala vrednost, kako bo delala z vašimi podatki in kdo bo dejansko izvajal projekt, je to opozorilni znak. Dober izbor pomeni manj tveganja, hitrejši ROI in večjo možnost, da AI res postane uporaben del vašega poslovanja.

Iskanje odgovora na vprašanje how to choose an AI agency je danes za številna podjetja pomembnejše kot samo vprašanje, kateri AI model uporabiti. Tehnologija napreduje hitro, toda razlika med uspešnim projektom in dragim eksperimentom je skoraj vedno v izvedbi. Prava agencija ne prodaja samo tehnologije, temveč pomaga opredeliti primer uporabe, preveriti kakovost podatkov, postaviti varovala ter iz prototipa narediti rešitev, ki deluje v praksi.

Pri M-AI d.o.o. opažamo, da podjetja najpogosteje ne potrebujejo “še enega AI orodja”, ampak partnerja, ki zna oceniti, kaj je smiselno avtomatizirati, kaj integrirati in kako iz tega ustvariti poslovni učinek. To velja tako za interne procese, pomoč uporabnikom, obdelavo dokumentov kot za bolj specializirane rešitve. Če vas zanima, kako pristopamo k takim projektom, si lahko ogledate storitve M-AI.

Zakaj je izbira prave AI agencije pomembnejša od samega demota

Demo je enostavno narediti impresiven. Z nekaj dobro pripravljenimi primeri je mogoče prikazati chatbot, avtomatizacijo ali analitiko, ki deluje skoraj brezhibno. Resnični izziv pa nastopi po podpisu pogodbe: ko je treba rešitev povezati z vašimi sistemi, očistiti podatke, urediti pravice dostopa, postaviti merila uspeha in zagotoviti, da rešitev deluje tudi čez tri mesece, ne samo na dan predstavitve.

Prav zato je pomembno, da agencijo ocenjujete po njeni sposobnosti izvedbe, ne po vizualni privlačnosti predstavitve. Po podatkih McKinseyja organizacije vse pogosteje uporabljajo AI, vendar to samo po sebi še ne pomeni vrednosti; uspeh je odvisen od tega, kako dobro je AI vpet v delovne procese in poslovni model McKinsey, The state of AI. Še bolj konkretno: Deloitte poroča, da je za večino podjetij največja ovira pri generativnem AI prehod iz pilotnih projektov v produkcijsko uporabo Deloitte, State of Generative AI in the Enterprise.

Z drugimi besedami: dober demo pokaže možnost. Dobra agencija pa pokaže pot do rezultata.

“AI is one of the most profound things we’re working on as humanity. It’s more profound than fire or electricity.”

Sundar Pichai

Takšna izjava zveni veliko in vizionarsko, vendar za podjetje ostaja ključno bolj praktično vprašanje: kdo bo to tehnologijo odgovorno in učinkovito uvedel v vaš poslovni kontekst?

7 opozorilnih znakov, da AI agencija morda nima pravega strokovnega znanja

  1. Govori samo o modelih, ne o poslovnih ciljih.
    Če je uvodni pogovor osredotočen izključno na modele, tokene, benchmarke in modne izraze, skoraj nič pa na KPI-je, procese in omejitve vašega podjetja, je to slab znak. Prava agencija najprej razume problem, šele nato izbira tehnologijo.
  2. Ne zna pojasniti dela s podatki.
    AI rešitev je tako dobra, kot so dobri podatki in njihova dostopnost. Če agencija ne sprašuje o virih podatkov, kakovosti, strukturi, dovoljenjih in upravljanju, obstaja velika verjetnost, da vas čaka nepredviden projekt.
  3. Obljublja univerzalno rešitev za vse.
    Vsako podjetje ima drugačne procese, druga tveganja in drugačno IT okolje. Agencija, ki vse projekte rešuje z enim istim “paketom”, verjetno ne razume kompleksnosti uvedbe AI v praksi.
  4. Ne omenja varnosti, zasebnosti in skladnosti.
    To je posebej pomembno pri delu z internimi dokumenti, uporabniškimi podatki ali reguliranimi procesi. IBM v svojih raziskavah redno izpostavlja, da so zaupanje, upravljanje in zmanjševanje tveganj ključni dejavniki pri širši uvedbi AI IBM, Global AI Adoption Index. Če agencija te teme preskoči, tvegate resne težave pozneje.
  5. Nima jasnega načrta merjenja uspeha.
    Če ne znajo povedati, kako bodo merili prihranek časa, zmanjšanje stroškov, povečanje kakovosti ali izboljšanje uporabniške izkušnje, potem tudi ne bodo znali dokazati vrednosti projekta.
  6. Ne pokaže konkretnih primerov izvedbe.
    Ni nujno, da razkrije vsa imena strank, mora pa znati predstaviti tipične scenarije, arhitekturo rešitve, izzive in rezultate. Na primer: kako je rešila obdelavo dokumentov, davčne procese ali avtomatizacijo prodajnih vsebin. Če vas zanimajo primeri specializiranih rešitev, si lahko ogledate FURS AI rešitev ali produktni primer Shelfze.
  7. Projekt vodi predvsem prodaja, ne izvedbena ekipa.
    Na začetku vsi zvenijo prepričljivo. Ključno vprašanje pa je, kdo bo projekt dejansko izvajal. Če ne spoznate strokovnjakov za arhitekturo, podatke, integracije in produktno implementacijo, kupujete obljubo brez jasne izvedbene osnove.

Po podatkih BCG je eden najpogostejših razlogov za zastoj AI pobud pomanjkanje operativne pripravljenosti in nezadostna integracija v procese BCG, AI Radar. To pomeni, da tehnična sposobnost sama po sebi ni dovolj; pomembna je celotna izvedbena disciplina.

Vprašanja, ki jih postavite pred najemom AI agencije

Če želite dobro primerjati ponudnike, si pripravite kontrolni seznam vprašanj. Tako boste hitro ločili agencije, ki prodajajo navdušenje, od tistih, ki znajo dostaviti rezultate.

1. Kateri poslovni problem boste reševali najprej in zakaj?

Dober partner bo predlagal ozek, smiseln prvi primer uporabe z jasnim potencialom učinka. Če agencija začne s preširokim projektom, je tveganje veliko.

2. Kako boste ocenili pripravljenost naših podatkov in sistemov?

Pričakujte konkreten odgovor: pregled virov, dostopov, formatov, kakovosti podatkov, integracij in pravnih omejitev.

3. Kaj bo merilo uspeha po 30, 60 in 90 dneh?

Prava agencija mora opredeliti mejnike, kot so funkcionalni prototip, validacija s končnimi uporabniki, natančnost, odzivni časi, stopnja avtomatizacije ali prihranek časa.

4. Kako boste poskrbeli za varnost in skladnost?

Vprašajte, kje se podatki obdelujejo, kako se hranijo, kdo ima dostop, kako se beležijo aktivnosti ter kako se obravnava občutljive informacije.

5. Kdo bo delal na projektu?

Zahtevajte imena ali vsaj vloge: vodja projekta, AI inženir, podatkovni strokovnjak, integracijski specialist, produktni vodja. To vam veliko pove o resnosti partnerja.

6. Kaj od nas potrebujete interno?

Pošten partner bo povedal, da brez sodelovanja vaših ekip ne bo šlo. Potrebovali boste lastnika procesa, dostop do ključnih ljudi, podatke in hitro odločanje.

7. Kako preprečite, da pilot ne ostane samo pilot?

To je eno najpomembnejših vprašanj. Agencija mora znati opisati prehod v produkcijo: monitoring, vzdrževanje, iteracije, odgovornosti, dokumentacija in usposabljanje uporabnikov.

“Most companies overestimate what AI can do in the short term and underestimate what it takes organizationally to make it work.”

Povzetek pogoste ugotovitve v industriji digitalne transformacije

Ta misel dobro povzema realnost trga. Tehnologija je pomembna, vendar je organizacijska izvedba pogosto odločilna.

Kontrolni seznam: kako praktično oceniti AI agencijo

Če želite hitro uporabno orodje za odločanje, si pomagajte s spodnjim seznamom. Pri vsakem ponudniku označite, ali je dokaz podan jasno, delno ali sploh ne.

Ta pristop je uporaben ne glede na to, ali iščete partnerja za generativni AI, avtomatizacijo dokumentov, interno bazo znanja, AI pomočnika za podporo strankam ali rešitev za specifične poslovne procese.

Kaj mora dober AI partner dostaviti v prvih 90 dneh

Najboljši odgovor na vprašanje how to choose an AI agency je pravzaprav zelo praktičen: izberite tistega, ki zna jasno opisati prvih 90 dni. Če tega ne zna, je verjetnost uspeha bistveno manjša.

Prvih 30 dni: diagnoza in prioritizacija

Rezultat te faze ni “ideja”, ampak strukturiran načrt. Dober partner bo povedal tudi, česa ne priporočajo avtomatizirati v prvi fazi.

Od 30 do 60 dni: prototip ali pilot z realnimi podatki

Pomembno je, da prototip ni samo “UI demonstracija”, ampak funkcionalen korak proti produkciji. V M-AI tak pristop pomeni, da že zgodaj preverimo, ali rešitev dejansko zmanjšuje ročno delo, pospeši procese ali izboljša dostop do informacij.

Od 60 do 90 dni: načrt za produkcijo in dokaz vrednosti

Do 90. dne bi morali vedeti tri stvari: ali primer uporabe deluje, kakšen je pričakovan poslovni učinek in kaj je potrebno za varno širitev. Če tega ni, je bil projekt verjetno preveč nejasno zastavljen.

Gartner pogosto izpostavlja, da vrednost digitalnih in AI pobud nastane šele, ko so te operacionalizirane v procese odločanja in dela Gartner, raziskave o AI in digital execution. To je tudi razlog, da je prvih 90 dni tako pomembnih: v njih se pokaže, ali imate pred sabo ponudnika ali resničnega partnerja.

Kako se izogniti najpogostejši napaki pri izbiri

Najpogostejša napaka ni, da izberete “napačno tehnologijo”. Najpogostejša napaka je, da izberete partnerja brez metodologije uvedbe. Mnoge organizacije kupijo AI projekt, preden opredelijo lastnika procesa, kriterije uspeha in dostop do podatkov. Posledica je dolgotrajen pilot brez jasne odločitve, kaj z njim storiti naprej.

Zato je smiselno izbrati agencijo, ki zna delati postopno: od poslovnega problema do pilota, od pilota do produkcije, od produkcije do optimizacije. Če pri tem potrebujete partnerja, ki združuje svetovanje, razvoj in konkretne AI produkte, je dober začetek pregled pristopa in primerov na m-ai.info.

Zaključek: izberite partnerja, ne predstavitve

Če povzamemo: pri izbiri AI agencije ne iščite najlepšega demota, temveč najbolj zrelega partnerja. Prava izbira pomeni, da agencija razume vaš poslovni cilj, zna oceniti podatke in procese, ima jasen načrt za prvih 90 dni, zna meriti učinek in odgovorno obravnava varnost ter skladnost. To je bistvo odgovora na vprašanje how to choose an AI agency.

Najboljši partner bo znal tudi odkrito povedati, kje AI ni prava rešitev. Ta iskrenost je pogosto bolj dragocena kot agresivna prodaja, ker kaže na resnično strokovnost.

Želite preveriti, ali je vaš AI primer uporabe pripravljen za izvedbo?

Če želite praktičen pogovor brez nepotrebnega hypea, nas kontaktirajte. V M-AI pomagamo podjetjem oceniti priložnosti, izbrati pravi primer uporabe, pripraviti pilot in ga pretvoriti v rešitev z merljivim učinkom.

Dogovorite se za uvodni pogovor prek kontaktnega obrazca in preverite, kako lahko AI varno in smiselno vključite v svoje procese.

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