According to the new “AI Self-Assessment Guide” developed by the technology consultancy h&k, one of the main problems lies not in the technology itself, but in the lack of reliable data, governance, prioritization, and adoption within companies. The guide identifies six major stages of maturity in AI adoption, ranging from organizations with disorganized or scattered data to companies that already have deployed solutions but have not yet managed to integrate them into their teams' daily operations.
“The market is full of promising initiatives that remain in the pilot stage and never reach real production. Many companies believe that the challenge is implementing AI, when in reality the real challenge is turning it into a sustainable capability, connected to the business and used by people,” explains Javier Tejada, co-president and head of technology at h&k.
From enthusiasm for AI to a real strategy
H&K's AI Self-Assessment Guide highlights that many organizations are entering a phase of accelerated enthusiasm for Artificial Intelligence without having yet resolved fundamental issues such as data quality, governance, or use case prioritization. Among the main symptoms identified by H&K are:
• Data distributed across multiple tools and systems.
• Lack of a single, reliable source of information.
• AI projects without clear prioritization criteria.
• Isolated pilots who fail to climb.
• Solutions deployed without real adoption by the teams.
• Risks associated with the uncontrolled use of AI tools within the organization.
According to Javier Tejada, “skipping steps often leads to solutions that don't scale, generate frustration, or fail to deliver a tangible business impact.” “AI cannot be approached as a collection of disconnected tests. A roadmap is needed that combines strategy, data, governance, operations, and cultural change. The order matters,” Tejada adds.
Six stages to understanding the true point of maturity
The “AI Self-Assessment Guide” proposes a practical model that allows organizations to identify their current situation and define priority steps to move forward strategically. H&K identifies six stages:
disordered or scattered data,
data without governance or quality,
interest in AI but without focus or prioritization,
clear use cases ready for implementation,
pilots who don't scale and technology without real adoption.
Each stage incorporates self-diagnostic indicators and specific recommendations for realistic and sustainable evolution. H&K's proposal: AI focused on business and real adoption. Through this guide, H&K reinforces its position as a strategic partner in Data & AI projects, supporting organizations from data strategy and governance to the industrialization and adoption of Artificial Intelligence solutions.
The consulting firm's offering includes services such as:
Data strategy and architecture,
Data governance and AI governance,
AI master plans,
Identification and prioritization of use cases,
Development and implementation of AI solutions,
Industrialization and scaling of initiatives and Training, leadership and change management.
H&K's ultimate goal is to help companies turn opportunities into measurable results, without hype and with discipline.
The AI Self-Diagnosis Guide can be downloaded at this link: https://hktech.es/guia-de-autodiagnostico-inteligencia-artificial
