ADaSci Launches AIDP to Set a New Standard for Enterprise AI Delivery

Enterprise AI is entering a phase where delivery, not experimentation, defines success. The question is no longer what can be built, but what actually makes it into production and delivers outcomes. At the centre of that shift is judgment. The ability to decide what to build, what to ignore, how to sequence delivery, and how to make systems work inside real workflows.

ADaSci is attempting to formalise what has so far remained informal and invisible. The launch of the AI Delivery Professional (AIDP) programme introduces a credential that rewards participation rather than tests judgment under real conditions.

Authored by AIM Research and conferred by ADaSci, AIDP positions itself as a professional standard for those accountable for taking AI from pilot to outcome.

At its core, AIDP is not a course. It is a single, high-stakes recognition for globally recognised AI Delivery Professional.

The distinction matters. Most certifications in AI measure recall. AIDP is designed to measure judgement. The kind that determines whether a model moves from a notebook into a live workflow, whether adoption happens inside existing systems, and whether value is realised before budgets are exhausted.

This is not aimed at engineers building models or teams governing them. The program defines a third role. The one who owns delivery.

The AI Delivery Professional is the person accountable when outcomes are on the line.

Find out more about AIDP here.

Defining the role

The program formalises what accountability looks like in practice.

An AIDP holder is expected to:

• Frame the decision that justifies an AI project
• Choose what to build, what to buy, and what to ignore
• Sequence delivery so value lands before the budget does
• Hold the line on data, risk, and reversibility
• Drive adoption within existing workflows, not outside them

This framing is deliberate because enterprise AI has struggled less with capabilities than with integration, incentives, and sequencing. AIDP is built around those fault lines.

Examined on real-world judgment

The examination reflects that reality.

Instead of theoretical questions, candidates face scenario-based scenarios. These are designed to mirror the kinds of trade-offs that emerge in production environments.

Who is it for?

The program targets practitioners already operating at the intersection of technology and business outcomes.

This includes AI product managers, delivery and program leads, solution architects, consultants, engineering managers, and transformation leaders. The common thread is ownership of outcomes, not just inputs.

A minimum of 5 years of experience is required. The indicative pass rate is set at around 35%, reinforcing the program’s positioning as a difficult, signal-heavy credential.

Click here to find out more about the eligibility requirements.

Five domains of delivery

Candidates are evaluated across five domains that map the lifecycle of enterprise AI:

• Frame the decision that justifies the project.
• Choose what to build, what to buy, what to ignore.
• Sequence delivery so value lands before budget does.
• Hold the line on data, risk, and reversibility.
• Engineer adoption inside the existing workflow.

Together, these form a body of knowledge that moves beyond model building to operational execution.

The Founding Cohort

The first cohort will sit for the examination on 08 October 2026 at Cypher, KTPO, Whitefield, Bengaluru.

The framing is explicit. There is no second first.

Founding AIDP holders will serve as the reference cohort, setting the baseline for what the designation represents going forward. 

From 2027, the program will move to quarterly global cohorts.

The credential itself is conferred post-examination, along with a post-nominal and holder mark.

Find out more about AIDP here.