Generative AI

The adoption rate of Generative AI is one of the fastest in history—ChatGPT reached one million users in just five days, compared to several weeks for TikTok or Instagram.

This is a transformative revolution, comparable to the arrival of the iPhone and mobile applications. With Generative AI, digital interfaces can finally become truly conversational, offering a level of interaction far superior to the rule-based chatbots of the 2010s. Generative AI also enables the creation of images, code, videos, 3D models, molecules, and all types of data. Virtually all white-collar professions will be affected, including IT, design, customer service, marketing, strategy, and support functions.

The potential for productivity gains is immense: many tasks will become significantly faster, and new value propositions will emerge. AI-powered image generation can amplify creativity, while an AI assistant sourcing responses from corporate documentation can revolutionize customer relations.

To capture this value, businesses must undergo an AI transformation—a journey that Onepoint initiated years ago, leading to the development of Neo, our own secure AI assistant.

This is why we support our clients at every stage of their AI transformation, helping them evolve into a fully AI-powered enterprise.

Our AI offerings step by step

Step 1 – Understanding Generative AI
Conducting a diagnostic assessment to help clients determine their AI adoption journey.

Awareness & Targeted Training
Providing customized training and AI literacy programs for different business groups, including operations, developers, data scientists, marketing teams, and project managers.
Step 2 – Experimenting with AI
Ideation and Use Case Prioritization
Leveraging our extensive use case repository, built from collaborations with over a hundred clients, to identify and prioritize AI opportunities.

Market Tool Experimentation
Testing leading AI tools to evaluate their impact on productivity and identify the most relevant users within the organization.

Support for Microsoft Copilot Deployment
Assisting in the implementation and adoption of Microsoft Copilot tools to enhance business processes.

Prototyping Secure Custom AI Solutions
Developing tailored, secure AI prototypes to address specific enterprise needs while ensuring data protection and compliance.
Step 3 – Industrializing AI
Development of Custom Secure Generative AI Tools
Creating tailored, secure generative AI tools built on the client’s proprietary data, ensuring data privacy and compliance.

Establishing an AI Factory
Setting up an AI Factory to industrialize the management, prototyping, integration, and large-scale deployment of use cases, including the technical foundation and governance framework.

Measuring and Managing AI’s Carbon Impact & CSR
Tracking and managing the carbon footprint and Corporate Social Responsibility (CSR) impact of AI deployments to ensure sustainable and responsible AI practices.

Integration of Regulatory Challenges
Incorporating regulatory requirements, especially the upcoming European AI regulation, to ensure compliance and ethical AI development.
Step 4 – Deploying an AI Operational Model
Operational Efficiency Plan for Maximizing AI Productivity Gains
Developing a comprehensive operational efficiency plan to ensure that AI systems deliver maximum productivity gains. This includes process optimization and aligning AI initiatives with the Target Operating Model (TOM) to drive value across the organization.

Change Management and HR Impact Assessment
Supporting change management processes and evaluating the HR impacts of AI, particularly in terms of Job and Career Path Management (GEPP), to ensure a smooth transition, address workforce concerns, and align talent development with AI advancements.