Productivity
AI-Powered Productivity Personalization for Knowledge Workers
2456.ai, a Swedish enterprise company, deploys MAP to personalize how knowledge workers adopt and use AI productivity tools.
The Challenge
Enterprise productivity tools are adopted unevenly. Some employees become power users within weeks; others never progress beyond basic features. Standard training programs deliver the same onboarding regardless of each worker’s technical background, role requirements, or learning pace. The result: low tool utilization, inconsistent productivity gains, and enterprise licenses that deliver a fraction of their potential value.
The Solution
2456.ai integrates MAP to personalize how each employee discovers and masters AI productivity capabilities. MAP’s Active Sensing assesses each worker’s current tool proficiency, role-specific needs, and learning preferences through structured interactions during their normal workflow. Calibrated Beliefs model each worker across knowledge (feature understanding), mindsets (comfort with AI tools), interests (which capabilities matter for their role), abilities (technical aptitude), and community (team workflows and collaboration patterns). Adaptive Pathways generate personalized adoption sequences that introduce features in the order most relevant to each worker’s daily tasks.
The Results
Workforce
Upskilling 90,000 Manufacturing Employees with Personalized Pathways
Tata Electronics deploys MAP to increase productivity and minimize attrition across a 90,000-person manufacturing workforce.
The Challenge
Tata Electronics operates manufacturing facilities with 90,000 employees performing complex assembly and quality control tasks. Standard training programs deliver identical instruction regardless of each worker’s prior manufacturing experience, education level, or learning pace. New hires from different backgrounds — experienced factory workers, vocational school graduates, career changers — all receive the same onboarding timeline. The result: inconsistent time-to-productivity, preventable errors during the learning curve, and attrition among workers who feel undertrained or unchallenged.
The Solution
MAP personalizes the upskilling journey for each of 90,000 employees. Active Sensing assesses each worker’s existing manufacturing competencies, safety knowledge, and technical aptitude during onboarding. Calibrated Beliefs model each worker across process knowledge, safety mindsets, quality standards, manual dexterity indicators, and team integration. Adaptive Pathways generate training sequences that build on what each worker already knows — an experienced assembler from another manufacturer gets an accelerated path focused on Tata-specific processes, while a first-time factory worker gets foundational safety and process training before advancing to specialized tasks.
The Results
Tata Electronics has committed $280K to MAP deployment. The process is designed to be replicable across Foxconn and other Tata plants, making this a template for large-scale manufacturing workforce personalization. Projected outcomes include reduced time-to-productivity for new hires, lower error rates during onboarding periods, and decreased attrition among workers who receive pathways matched to their learning needs.
