NTT Data expands Google Cloud partnership, aims APAC cloud business to grow over 10x

Digital business and IT services company NTT Data on Monday said it currently has 2,600 Google-certified engineers in 50 countries and plans to certify at least 1,000 more in the Asia-Pacific region, while aiming to grow its cloud business in APAC by over 10 times in three years.

The company also announced the expansion of its strategic partnership with Google Cloud to accelerate the adoption of cloud-based data analytics and generative AI solutions for customers across key markets in Asia Pacific.

“This isn't just about adopting new technologies; it's about reimagining what's possible for businesses in the AI age. Our partner ecosystem is a cornerstone of our growth strategy, and this collaboration with Google Cloud is expected to grow our cloud business in APAC by over 10 times in 3 years,” said John Lombard, CEO, NTT Data, APAC.

NTT Data and Google Cloud aim to develop cloud-based data and AI solutions tailored to industry-specific needs. NTT Data said it will hire and upskill sales, pre-sales and delivery professionals on Google Cloud, equipping them to effectively sell, build, secure, migrate and deliver joint solutions to benefit customers.

According to Gartner, worldwide end-user spending on public cloud services in 2024 is forecast to total $679 billion and is projected to exceed $1 trillion in 2027.

Generative AI (GenAI) deployments across organizations will further fuel the growing demand for modern cloud infrastructure, highlighting the importance of this strategic partnership launched in APAC, with plans for global expansion, according to the report.

"Customer confidence is paramount to deliver on their digital transformation aspirations, and NTT Data's comprehensive portfolio, coupled with a deep understanding of evolving customer needs across Asia Pacific, perfectly complements Google Cloud's AI leadership and innovative solutions,” said Karan Bajwa, Vice President, Google Cloud, APAC.

As generative AI relies heavily on high-quality data for training and insights, robust data analytics capabilities are essential for successful deployments.