April 8, 2025

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IBM Acquires Hakkoda to Boost AI Capabilities, EU AI Act Takes Effect

IBM has acquired Hakkoda, a global data and AI consultancy, to expand its data transformation services and support AI-driven operations. This move is part of IBM's efforts to ramp up its investments in AI and automation technologies, which has led to significant growth, with AI bookings and sales reaching over $5 billion in Q4 2024. The acquisition aims to help clients prepare their data for AI-powered business operations and build integrated enterprise data estates. Meanwhile, the EU AI Act introduces a risk-based framework for AI systems, and UK businesses must comply to compete in the European market. Other developments in the AI space include the rise of Agentic AI, which has the potential to become a powerful driver of intelligent decision-making, problem-solving, and innovation. Additionally, Google is paying some AI staff to do nothing for a year rather than join rivals, and researchers are making progress in developing self-improving AI models, AI therapists, and small language models. The AI market is expected to continue growing, with the United Nations warning that artificial intelligence will affect 40% of all jobs in the world in the coming years.

IBM buys Hakkoda to boost AI services

IBM has acquired Hakkoda, a global data and AI consultancy, to expand its data transformation services and support AI-driven operations. Hakkoda will bring its expertise in data platforms and AI-powered assets to IBM Consulting. The acquisition aims to help clients prepare their data for AI-powered business operations and build integrated enterprise data estates. IBM will gain hundreds of experts across the US, Latin America, India, Europe, and the UK, and access to Hakkoda's strong portfolio of generative AI-powered assets.

IBM buys Hakkoda to boost AI services

IBM has acquired Hakkoda, a global data and AI consultancy, to expand its data transformation services and support AI-driven operations. Hakkoda will bring its expertise in data platforms and AI-powered assets to IBM Consulting. The acquisition aims to help clients prepare their data for AI-powered business operations and build integrated enterprise data estates. IBM will gain hundreds of experts across the US, Latin America, India, Europe, and the UK, and access to Hakkoda's strong portfolio of generative AI-powered assets.

IBM acquires AI consultancy Hakkoda

IBM has acquired Hakkoda, a data and AI consultancy based in New York, to further expand its ability to bring consultants and AI to clients. Hakkoda's expertise in data platforms and AI-powered assets will be added to IBM Consulting's data transformation services portfolio. The acquisition is part of IBM's efforts to ramp up its investments in AI and automation technologies. IBM's strategy has led to significant growth, with AI bookings and sales reaching over $5 billion in Q4 2024.

IBM enhances AI consulting with Hakkoda deal

IBM has acquired Hakkoda to boost its data transformation services and support AI-driven operations. The deal strengthens IBM Consulting's ability to deliver high-performance, AI-ready data solutions for clients. Hakkoda's expertise in data platforms and AI-powered assets will help clients prepare their data for AI-powered business operations. The acquisition is expected to strengthen IBM's capacity to meet the rising demand for data services and enable clients to build integrated, high-performance data estates.

IBM announces Hakkoda acquisition

IBM has acquired Hakkoda, a global data and AI consultancy, to expand its data transformation services portfolio. Hakkoda will add specialized data platform expertise to help clients get their data ready to fuel AI-powered business operations. The acquisition closed on April 2, 2025, and financial details of the transaction were not disclosed.

EU AI Act implications for UK businesses

The EU AI Act introduces a risk-based framework for AI systems, classifying them into four categories: minimal, limited, high, and unacceptable risk. UK businesses must comply with the Act to compete in the European market. The Act requires a thoughtful data migration strategy and a modern, multi-use case data platform on the cloud. UK businesses can adopt international standards like ISO 42001 to ensure compliance and build trust among customers, partners, and regulators.

Rise of Agentic AI

Agentic AI is a new phase of AI that goes beyond making existing workflows more efficient and moves toward replacing existing workflows and creating new ones. Truly autonomous AI agents can act autonomously, make decisions, and adapt dynamically. Companies will need to address regulatory challenges, build AI literacy, and focus on applied use cases with clear ROI to succeed in this era. Agentic AI has the potential to become a powerful driver of intelligent decision-making, problem-solving, and innovation.

Google pays AI staff to do nothing

Google is allegedly paying some AI staff to do nothing for a year rather than join rivals. The company is using aggressive non-compete agreements to retain top AI talent. Some AI staff are paid during this time, but the practice can make researchers feel left out of the quick pace of AI progress. Google's AI division, DeepMind, has resorted to using these agreements for some AI staff in the UK.

DeepSeek and Tsinghua develop self-improving AI models

DeepSeek and Tsinghua are working together to develop self-improving AI models that require less training data and computational resources. The collaboration aims to reduce the operational costs of AI models and make them more efficient. DeepSeek, a Chinese startup, has collaborated with researchers from Tsinghua University to develop a novel approach to reinforcement learning.

AI therapist shows promise

New research suggests that AI bots can deliver mental health therapy with as much efficacy as human clinicians. The AI therapist, developed by researchers from Dartmouth College, uses a unique approach to address mental health issues. The study found that people who used the AI therapist showed significant improvement in their mental health symptoms. The AI therapist has the potential to address the shortage of mental health providers and provide accessible mental health care.

Future roles in healthcare AI

The MD/MS in AI dual degree program at UT Health San Antonio aims to generate chief AI officers, clinical AI implementation specialists, healthcare data scientists, and AI consultants. The program is designed to address the growing need for AI expertise in healthcare. Dr. Ronald Rodriguez, professor of urology, believes that the program will help create a new generation of healthcare professionals who can develop and implement AI solutions.

Small language models explained

Small language models (SLMs) are smaller versions of large language models that offer reduced costs while performing at par or even outperforming larger models. SLMs have fewer parameters, but can still be powerful and are well-suited for specific tasks. They require less computing power and can be deployed on personal computers or devices, making them faster, cheaper, and easier to fine-tune for specific business needs.

AI coding assistant gains popularity

Cursor, an AI-infused code editor, has gained a million users without spending a single dollar on marketing. The platform offers a unique interface and support for a wide range of large language models, making it a popular choice among software programmers. Cursor's success is attributed to its ability to analyze a programmer's actions and suggest the next few lines of code, making it a valuable tool for developers.

AI startup secures big-name backers

Rescale, an AI physics modeling company, has secured a $115 million Series D funding round with support from big-name backers, including Sam Altman, Jensen Huang, and Jeff Bezos. The company aims to help clients run physics simulations 1,000 times faster using AI and data science. Rescale's new round is part of a trend of increased investment in AI, with 71% of total deal value in Q1 2025 attributed to AI.

AI to impact 40% of all jobs

The United Nations warns that artificial intelligence will affect 40% of all jobs in the world in the coming years. The market value of AI is expected to reach $4.8 trillion by 2033, but the benefits of this technology will remain concentrated in just a few companies. The UN report highlights the potential for AI to cause unemployment and inequality, and offers recommendations to foster inclusive development, including public disclosure of information about AI and the creation of a common infrastructure for AI.

Key Takeaways

  • IBM has acquired Hakkoda, a global data and AI consultancy, to expand its data transformation services and support AI-driven operations.
  • The acquisition aims to help clients prepare their data for AI-powered business operations and build integrated enterprise data estates.
  • IBM's AI bookings and sales reached over $5 billion in Q4 2024, driven by its investments in AI and automation technologies.
  • The EU AI Act introduces a risk-based framework for AI systems, and UK businesses must comply to compete in the European market.
  • Agentic AI has the potential to become a powerful driver of intelligent decision-making, problem-solving, and innovation.
  • Google is paying some AI staff to do nothing for a year rather than join rivals, using aggressive non-compete agreements to retain top AI talent.
  • Researchers are making progress in developing self-improving AI models, AI therapists, and small language models.
  • The AI market is expected to continue growing, with the market value of AI expected to reach $4.8 trillion by 2033.
  • The United Nations warns that artificial intelligence will affect 40% of all jobs in the world in the coming years, highlighting the potential for AI to cause unemployment and inequality.
  • AI has the potential to address the shortage of mental health providers and provide accessible mental health care, with AI therapists showing promise in delivering mental health therapy with as much efficacy as human clinicians.

Sources

AI Artificial Intelligence Machine Learning Deep Learning Data Science IBM