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AI ready blueprint: succeed before you start (43 chars)

AI Ready Blueprint: Where to focus for AI success

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Why are most AI projects failing?

Right now, organizations worldwide are making the same expensive error: implementing AI projects without asking the right questions before they begin.

Over 50% of generative AI projects are failing, with at least 30% likely to be abandoned after proof of concept by the end of 2025.¹

Companies invest $5-20 million developing custom models, plus $8,000-$21,000 per user annually² — only to discover their initiatives cannot scale beyond pilot programs.

The stark reality

But AI isn’t to blame.

The difference isn't choosing the technology.

It's asking the right questions before you begin.

Through extensive client implementations across every major cloud platform, SoftwareOne has identified six strategic questions that measurably separate AI successes from expensive failures. Get these questions right, and you could join the successful minority enjoying substantial business advantages from their AI deployments.³

Six questions that answer (almost) everything

  • Number 1 icon

    Why are we implementing AI?

    Are you implementing AI for AI's sake, without clear business objectives?

  • Number 2 icon

    Where should we host our data?

    Is your data trapped in legacy systems?

  • Number 3 icon

    What state is our data in?

    How good (or bad) is your data quality?

  • Number 4 icon

    How will we govern AI?

    Do you have governance frameworks in place to protect your data and optimize your budgets?

  • Number 5 icon

    Who are our critical stakeholders?

    Have you selected business line champions to identify specific operational challenges and drive solutions forward?

  • Number 6 icon

    When should we implement AI?

    Do you understand why strategic sequencing is a better implementation strategy for many AI deployments?

AI: Succeed before you start

SoftwareOne's systematic approach to AI readiness has guided successful implementations across many industries, consistently transforming AI potential into measurable competitive advantage. Rather than joining the statistics of failed AI projects, organizations can leverage proven frameworks to flatten the AI learning curve and achieve sustainable success. The choice is clear: systematic preparation or expensive disappointment.

Start building your AI ready blueprint. Today.

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White Paper (@40 min read)

AI-Ready Blueprint: Six questions to help your AI project succeed before it starts

A complete framework with detailed guidance and case studies covering AWS, Azure, and Google Cloud, plus proven implementation methodologies you can use immediately.

Essential insights for busy leaders

Key insights, critical statistics, and actionable next steps distilled into a quick-read format you can review this week.

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Executive Summary (@10 min read)

Connect with our AI experts today

Explore these questions in the context of your own organization’s individual plans and projects.

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References
¹ A third of all generative AI projects will be abandoned, says Gartner, ZD Tech Today; 
The wrong ways to implement AI: Learning lessons from others' mistakes, SoftwareOne
² Gartner via TechRepublic, 2024
³ Superagency in the Workplace, McKinsey, 2025