A promising idea still has to earn its place in the portfolio. We compare business value, feasibility, evidence, risk, and delivery capacity so your leaders can decide what to test, fund, pause, or stop, then see what each choice depends on.

Some of the 500+ brands we've worked with. Our delivery runs on 100+ AI workflows in production.

See all references

Weigh opportunities, costs, roadmap sequencing, ownership, and vendor choice as 5 separate calls, each with its own evidence and method.

Decide & Govern

AI OpportunityPortfolio Assessment

Every team has an AI idea, and most lists grow faster than anyone can vet them. We work through yours until each use case carries a pursue, test, park, or reject call with the evidence, uncertainty, dependencies, and owner visible behind it.

Portfolio assessment fits when AI ideas compete for funding and each needs an evidence-backed pursue, test, park, or reject decision with an owner.

AI Business Case& ROI Modeling

One appealing ROI figure rarely survives a finance review. We build the case from your current costs, a credible non-AI alternative, and assumptions stated in the open, so the model shows a range and the conditions the return depends on.

Build the business case when strategy needs a finance-approved baseline, credible non-AI alternative, explicit assumptions, and downside-to-upside return scenarios.

AI TransformationRoadmap

A roadmap becomes useful when it shows what must happen first and what would justify the next investment. We order the capability, data, governance, people, and delivery work behind your priority outcomes, then mark the evidence your leaders will use to scale, pause, or stop each wave.

The roadmap fits accepted priorities that still need dependency-ordered waves across data, governance, people, and delivery, each with an investment gate.

AI OperatingModel Design

AI work can stall when nobody knows who can fund, approve, or stop it. We assign those decision rights across sponsorship, delivery, review, operation, and value ownership, and connect them through governance handoffs that hold up under pressure.

Operating-model design fits when AI strategy stalls between funding, delivery, review, operation, and value ownership because decision rights and handoffs are unclear.

AI Vendor, Model& Platform Selection

Feature lists make every option look capable. Your constraints decide which one actually fits. We compare the shortlist against the business, technical, risk, and operating realities you named, and the recommendation keeps its evidence, exceptions, dependencies, and decision owner attached.

Select vendors, models, or platforms when strategy has a real shortlist and needs representative tests, weighted constraints, unsupported-claim tracking, and accepted trade-offs.

Scattered pilots compete for the same budget, often without a shared view of value, evidence, dependencies, or risk. We put the choices on the table, including the ideas that need to wait or stop.

We work from the outcome, the current workflow, your constraints, and the strongest non-AI alternative. Every recommendation keeps its assumptions, evidence, owner, and next investment gate attached.

Every recommendation keeps its assumptions, evidence, owner, and next investment gate attached to it.

Business owners set out the outcomes, current AI activity, workflows, data and technology constraints, and who holds authority over the resulting choices; each candidate is then examined for value, feasibility, evidence, user impact, risk, and the strongest available non-AI alternative. Zeo orders the dependent work — pilots, data and integration work, governance controls, operating responsibilities, measurement plans — around the dependencies teams will actually face, and records for every pilot the evidence it must produce, the conditions for stopping or scaling, and the person who makes the next funding call. Ideas that should wait or stop are named as such rather than left on a list.

The list gets smaller as the evidence gets better.

Establish the decision context
Business owners show us the outcomes, current AI activity, workflows, data and technology constraints, and who has authority over the resulting choices.
Put the candidates side by side
Each use case is examined for value, feasibility, evidence, user impact, risk, and the strongest available non-AI alternative.
Order the dependent work
Pilots, data and integration work, governance controls, operating responsibilities, and measurement plans are arranged around the dependencies teams will actually face.
Agree what earns the next decision
For every pilot, we record the evidence it must produce, the conditions for stopping or scaling, and the person who makes the next funding call.

Every operational consultant at Zeo has secure LLM access and training, and AI sits inside the daily work. Five of them came through our AI Bootcamp and wrote down what they expect it to change.

I see generative AI having an enormous effect on daily life and on every industry it touches. As the technology develops, the range of uses will keep widening across creativity, problem-solving, and innovation. We can already see that range in realistic image, video, and music production, pharmaceutical research, and design. I expect the effect on industries to become profound. E-commerce, healthcare, finance, and many other sectors will be able to create more engaging, personalized experiences and make their processes more efficient.

The ability to produce unique content and solutions will open new possibilities and increase efficiency.

Ozan Ketenci

Generative AI has the potential to transform SEO, digital marketing, and many other sectors. I expect it to play an important role in our lives in the near future, with more personal experiences, more effective marketing, faster interpretation of data, and quicker action. Products and services will improve. Processes such as customer communication will become more efficient, and organizations that fail to keep up will fall behind businesses that bring AI into their work.

Organizations should start planning the AI applications that make sense for their sector now.

Samet Özsüleyman

We may be at a moment as significant as the computer revolution, with the potential to transform businesses and industries. Yet for many people, generative AI still means opening a tool such as ChatGPT for a task at work or in daily life. That is only the surface. Companies that integrate generative AI models into workflows and customer processes, and go beyond content production, will gain huge competitive advantages in the coming years.

I believe generative AI should be on the agenda of every board of directors as soon as possible.

Hande Parmaksız

I see artificial intelligence as the most exciting technology of both the present and the future. Its potential is unlimited, and we're still at the tip of the iceberg. AI is developing quickly, while much of what it could mean for different sectors remains unexplored. The effect on digital work is already substantial. In the years ahead, I expect breakthroughs that change how entire industries work.

AI's potential will keep expanding. No sector can afford to ignore the opportunity for efficiency and progress. We will keep discovering new dimensions, and I don't see a saturation point.

Can Mutioğlu

Work by major technology companies is likely to give generative AI a much wider role in the years ahead. It will create new dynamics in art and design, as well as in sensitive fields such as healthcare and finance. As the technology becomes part of daily life, the ethical and risk questions will grow with it. Being able to follow and experience those developments up close is what makes generative AI so exciting to me.

I look forward to seeing more uses of generative AI that benefit society.

Ezgi Gülsen Yaylı

Three speakers look at the pace of AI change and what it means for e-commerce and content teams.

The Future Will Come Faster Than You Imagined

Yiğit Konur, Wope

Effective Use of AI for E-Commerce Companies

Burak Pehlivan, Wope

Producing Content Compatible with Google Algorithms with AI

Mert Erkal, Stradiji

Agents, chatbots, and RAG systems at Zeo are built by senior engineers who keep operating them after launch. The consultants below are those builders, matched to the work this page covers.