Emergn offers Value-Driven AI Adoption Service

Emergn has designed a new advisory service aimed at helping organisations advance from AI experimentation to build defensible engines of growth using scalable AI solutions. The new capability, Value-Driven AI Adoption, targets large organisations that struggle to turn AI pilots into production at scale.

An MIT Media Lab report highlights the challenge. Finding that “95% of organisations are getting zero return” from Generative AI projects. Emergn’s own report, “The Global Intelligent Delusion,” was more positive. It highlighted that 77% expect new AI solutions to drive revenue in the next 12 months.

The question is, what will change this statistic? Emergn found that 55% of leaders identified three barriers to success: lack of talent, problem framing, and a lack of outcome-focused design.

The delusion is that organisations think that every AI project will succeed and transform their organisation. The reality is that certain foundations need to be in place. It is those foundations that the new service aims to improve.

Value-Driven AI Adoption targets three things simultaneously:

• How AI is governed
• How it is delivered
• How the capability to do both is built inside the client organisation

Alex Adamopoulos, Chairman and CEO of Emergn, commented, “Value-Driven AI AdoptionThe winners will be the ones who turn AI into growth, with AI contribution margin as the new scoreboard. That’s what Value-Driven AI Adoption is built to deliver.”

How Value-Driven AI Adoption Works

Emergn divides the engagement into three phases using a vendor-agnostic model. However, Emergn’s Value, Flow, Quality (VFQ) philosophy underpins the approach. With Praxis, the firm’s product development platform powered by Stella, its AI product coach, supporting it. Agnosticism means that customers can use their chosen models, cloud and AI technology within the engagement. Therefore, Emergn provides the methodology for success rather than the technology and technical expertise.

Phase 1: Diagnostic
The engagement starts with a one-week diagnostic, offered at no cost and with no obligation. This phase includes executive interviews, a current-state assessment, a strategy heat map, and the identification of three to five priority use cases, giving senior leaders a clear view of where AI can deliver the greatest impact.

Phase 2: Operating model
The second phase, typically delivered over two to seven weeks, puts the foundations in place for scalable adoption. It defines governance, value frameworks, AI leadership structures, operating models, and sandbox strategies needed to support AI at scale.

Phase 3: Validation and scale
The third phase validates value through the first AI Board cycle, captures reusable assets and practices, and delivers a practical six- to 18-month roadmap to help organisations sustain and scale AI adoption internally.

What happens with Value-Driven AI Adoption

The engagement aims to change how organisations approach AI projects. It achieves this across three dimensions:

• Prioritise AI investments based on measurable business outcomes. Clients move from a sprawl of pilots to a focused, defensible portfolio of use cases, prioritised through a value framework and governed by a standing AI Board giving senior leadership confidence to fund what’s working and stop what isn’t.
• Activate a target operating model for AI at scale. Clients put in place the structures that make AI repeatable – a Centre of Excellence, a sandbox strategy, and governance designed to unlock speed safely rather than slow delivery down.
• Prove the model and own it. One to three high-priority use cases are delivered through the new operating model, the first AI Board cycle is run end-to-end, and reusable assets, playbooks, and a 6–18 month roadmap are handed over for the client’s teams to own and extend.

Within a year of commencing the engagements, Emergn believes that it can demonstrate revenue gains from AI projects. You can use those projects to build business cases for further investments based on those outcomes. The organisation should have an AI board in place that gives the main board the confidence to continue investing in value-driven AI projects.

Furthermore, the organisation should be in a position where it has grown AI muscles internally in the form of people, communities and assets that it can continue to leverage in the future.

Adamopoulos added, “The tools work. The wrappers around them don’t yet. Capable organizations and capable people shouldn’t be left behind because the operating model can’t keep up with the technology. AI should multiply what your people do – not be rented from consultants who leave with the capability when the engagement ends.”

Enterprise Times: What does this mean

Emergn has a very different approach to many consultancies; it aims to change how organisations work at a fundamental level. Rather than successfully delivering projects. The Value-Driven AI Adoption capability enables organisations to continue delivering AI projects long after the initial engagement ends.

However, the lack of customer examples and quotes from participants limits this announcement. Hopefully, Emergn will be able to reveal some case studies and successes in the near future.

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