AI adoption tends to succeed in each boardroom agenda quicker than anticipated, propelled by urgency, aggressive strain, and a rising sense of FOMO. This text captures highlights from a current dialogue between Mike Zamarski, Digital Transformation Advisor, and Adam Grabek, Options Architect at Future Processing, the place they explored in full what it means to be AI-ready, why legacy doesn’t should be a blocker, and the way organisations are already attaining outcomes similar to 2.5x quicker response occasions with AI.

Future Processing

Stakeholders count on quick solutions from decisionmakers: which platforms to make use of, which distributors to decide on, and which instruments to implement to generate fast wins.

The strain to simply begin with one thing, and begin with it quick, overrides any evaluation of whether or not the organisation is able to make their subsequent huge AI initiative really work.

The unsuitable place to begin

In the meantime, the market actuality is harsh. In keeping with business knowledge, 70 to 80% of AI initiatives fall wanting their said targets, a determine persistently echoed in analyses by McKinsey or Gartner.

When organisations prioritise execution over preparedness, AI turns into much less a lever for transformation and extra a catalyst for current inefficiencies. The true supply of the issue lies elsewhere.

AI is a multiplier of what you have already got…

…and this dynamic cuts each methods. When pursuing AI adoption and not using a steady operational baseline, the tech serves as an amplifier of inconsistency reasonably than a drive for decision. With out visibility into your operations, AI stays indifferent from the levers that drive efficiency and worth. You possibly can’t effectively optimise what you possibly can’t see or align what nobody agreed to trace within the first place.

Modernising for AI with out metrics is like asking Google Maps for instructions with out enabling GPS in your cellphone.

It’s not the algorithms that carry AI initiatives down, however the absence of a shared view of the present state, and of what measurable progress ought to seem like.

Legacy, too, doesn’t should be a blocker, offered it’s addressed by means of structured modernisation method, the place visibility and metrics type the groundwork for each fast wins and sustainable worth.

And a complete metrics-driven method affords the construction wanted to outline, monitor and align each fast wins and sustainable worth.

Complete-metrics pushed method to AI adoption

A metrics-driven method provides management one thing to steer by and course-correct alongside the AI adoption course of, with clear visibility into present operations, measurable progress, and the remaining floor to cowl.

Future Processing

What must be measured earlier than AI will be adopted for worth

Acquire readability on how programs operate, how processes run, and the way choices are made throughout groups.
Related indicators embrace guide interventions ratio, KPIs alignment with precise system output, and common time-to-decision.

Establish inconsistencies in workflows, knowledge definitions, and accountability.
Helpful metrics would possibly cowl the proportion of guide reconciliations, conflicting income definitions, and shadow reporting programs.

Outline what failure means as clearly as success standards. Set it at the beginning of each initiative. That means it serves because the early sign of drift, not the closing observe of a autopsy.
Key measures might embrace rising error charges, repeated SLA breaches, or an rising share of rework attributable to poor knowledge high quality.

These metrics make it easier to acknowledge uneven readiness and allow phased, observable rollout.
Observe it by means of the share of AI-supported workflows, rising variety of choices backed by predictive fashions or availability and high quality of coaching knowledge.

These metrics expose whether or not the organisation is genuinely ready to operationalise AI or merely participating in optimistic spending with out the required foundations.

Future Processing

AI can’t ship with out measurable foundations

In FOMO-fuelled boardrooms, a metrics-first AI technique could appear sluggish, cautious and even counterintuitive. In the long term, nonetheless, it’s the one path to sturdy worth, the place choices are traceable and outcomes endure means past the mission launch.

The webinar expands on this attitude,  exhibiting how metrics can flip AI adoption from cautious experiments into accountable transformation, with outcomes already seen in main organisations.

In regards to the writer: Mike helps corporations flip ambition into measurable outcomes. With over a decade of expertise partnering with C-level executives worldwide, he drives enterprise transformation by means of technique, AI implementation, and scalable collaboration fashions. His work contains designing change frameworks, main GenAI adoption initiatives, and co-creating an inner consulting guild to strengthen advisory capabilities.