Founder Voices: Global Vision, Local Action with the Founders of Pakufi
Founder Voices: Episode 2 — Global Vision, Local Action with Pakufi
In this episode of Founder Voices, Clement Akran speaks with the founders of Pakufi, an ethical tech agency dedicated to creating solutions that are both globally impactful and locally rooted.
Their conversation explores how purpose-driven innovation, strong community ties, and ethical leadership are shaping the future of technology.
Listen in for real-world insights, lessons from the start-up journey, and practical advice for founders building with heart and vision.
Power Is Shifting — What It Means for Startups, SMEs and Charities
Power is shifitng and what it means for startups, SMEs, and charties
CIO Vision 2025: Bridging the Gap Between BI and AI
This MIT Technology Review Insights report, sponsored by Databricks, explores how CIOs are driving AI adoption in their organizations. Based on a global survey of 600 technology leaders, the report finds that companies are moving from limited AI use to widespread adoption across core business functions by 2025.
However, scaling AI successfully requires overcoming challenges such as data management shortcomings, internal rigidities, and talent deficits. The report highlights key priorities for CIOs, including:
Investing in data foundations: Improving data processing speeds, governance, and quality.
Scaling AI use cases: Driving innovation and efficiency across different functions.
Aligning data strategy with AI ambitions: Ensuring data capabilities support AI goals.
Unlocking AI's Potential: Three Pillars of Success
Unlocking AI's Potential: Three Pillars of Success
AI and machine learning (ML) hold immense promise, but many organisations struggle to realise tangible benefits. This article explores the three critical factors that underpin successful AI initiatives:
Data Foundation: A robust data foundation is crucial, enabling proactive planning and effective responses to market changes.
Scaling ML: Democratising access to data and empowering individuals across the organisation to leverage data for informed decision-making is essential. This involves embracing open standards and enabling data consumers to easily perform data exploration and generate ML models.
Simplified MLOps: Streamlined MLOps are essential for accelerating the ML lifecycle and ensuring the use of the most current and reliable data. This involves unifying data and ML models, providing end-to-end processing, and fostering collaboration.
