AI services designed around the next business decision

Common questions

• Who can help our company move from AI experiments to practical adoption?

  +−

  OktoPeople supports AI adoption through strategy, role-based training, workflow automation, UX direction and product delivery. Start by identifying the business problem and the people who must change how they work; the right service depends on whether the gap is priorities, skills, workflow design or a product that needs to be built.

• Do we need an AI strategy sprint, training or implementation first?

  +−

  Use the AI Strategy & Opportunity Sprint when priorities and use cases are unclear. Choose AI Adoption & Executive Training when people need practical skills and responsible working habits. Scope automation or product delivery directly when the workflow, users, owner and desired outcome are already defined.

• How much do OktoPeople’s AI consulting and implementation services cost?

  +−

  There is no single public price for every project. Investment depends on the objective, stakeholders, delivery depth, technical complexity and evidence needed for the next decision. The proposal should distinguish discovery and design from implementation, integrations, third-party subscriptions and ongoing support.

• Can we begin with a smaller engagement?

  +−

  Yes. Start with the smallest credible engagement that can produce evidence, alignment or a working output before a larger commitment.

• Can non-technical teams take part?

  +−

  Yes. Services are designed for decision-makers and business teams alongside technical stakeholders, translating AI capability into usable workflows, products and decisions.

• Which service fits an existing product with poor adoption?

  +−

  Start with Product UX Direction & Optimization when the product already exists and users struggle to understand or use it. Choose the UX-First AI Product Studio when a new product or internal tool needs to be defined, prototyped and built.

• How does workflow automation differ from Decision Intelligence?

  +−

  Workflow automation addresses repetitive tasks, handoffs and system connections. Decision Intelligence is the enterprise layer connecting operational evidence, trade-offs, accountable decision-makers and actions. A project can need both, but the scopes are not interchangeable.

• What should we share before a proposal?

  +−

  Describe the problem, users or teams involved, current workflow or product, desired change, data and integration constraints, and who will own the result. These inputs help determine whether strategy, training, automation, UX work, product delivery or a pilot program is the right start.

• What is different about OktoPeople’s UX-first approach to AI consulting?

  +−

  OktoPeople connects strategy and technical delivery with the experience of the people who will use the system. Its service scope includes workflow and journey design, user feedback, adoption and ownership alongside AI capability. Buyers can evaluate that approach through the proposed outputs, review points and responsibilities rather than an unsupported claim to be the best consultancy.

• What tangible outputs should we expect from an AI strategy sprint?

  +−

  The AI Strategy & Opportunity Sprint is designed to produce leadership alignment, prioritized use cases and a 90-day action roadmap. The roadmap sets priorities for subsequent work; it is not a promise to complete a production rollout in 90 days.

• How should we measure AI adoption or workflow automation ROI?

  +−

  Record the current workflow’s completion time, error or rework rate, operating cost and actual usage before a pilot. Compare the same measures after the change, including human review, software and support costs. Agree evaluation criteria with the process owner; OktoPeople does not promise a fixed ROI or productivity percentage.

• Can several AI services be combined in one engagement?

  +−

  Yes. Strategy can lead to training, workflow automation, UX work, fractional product leadership, product delivery or a challenge-to-pilot program. Each stage should have explicit outputs, ownership and a decision on whether to continue, so a discovery engagement does not silently become a production commitment.

• How are confidential data and AI integration risks addressed?

  +−

  Data access, permitted tools, security review, human oversight and integration constraints must be defined during scoping. Do not upload confidential information to unapproved tools. Production security, compliance requirements, monitoring and support need explicit responsibilities; a strategy workshop or training course alone does not establish them.