Pure Storage forecasts AI will be the most dominant tech moulding the technology landscape in the APJ region. We can expect significant shifts in 2025 in the way businesses invest and utilise AI, as we swing towards a more mature AI environment
Data storage tech solutions provider Pure Storage has shared its seminal tech outlook for 2025.
Pure Storage predicts that while AI will continue to shape the technology landscape in Asia Pacific and Japan region (APJ), 2025 will bring significant shifts in the way that organisations invest and utilise AI as the region moves towards a more mature AI environment. Pure Storage also expects sustainability to return to becoming a top 3 priority for companies while cybersecurity strategies move towards data protection.
Pure’s Predictions for 2025:
Industrial AI will take off as the next AI wave in 2025
In 2025, we will see the next wave in this current AI revolution. Market observers estimate that most GPUs deployed are currently severely underutilized. Additionally, the majority of GPUs are deployed in a handful of companies, including the hyperscalers, with very few in private enterprises. This will shift in 2025, as enterprises bring much of the AI capability in-house to extract even more value out of their data and “industrialise” AI. We call this Industrial AI, which brings its own set of challenges including governance – specifically around how to train the models with proprietary data that needs to be kept confidential even between departments. Agentic AI and Large Quantitative Models (LQMs) will play a key role in this wave.
“As India continues its rapid digital transformation, 2025 will mark a pivotal year for organisations to embrace Industrial AI and advanced data-centric strategies. At Pure Storage, we are committed to helping businesses in India unlock the true value of their data while navigating challenges like AI governance, sustainability, and cybersecurity.”
Ramanujam Komanduri, Country Manager, Pure Storage India
Machine Learning & Agentic AI will transform decision making in enterprises in 2025
While we expect Agentic AI to only become mainstream from 2026 onwards, Agentic systems will change the way AI is used for decision making in enterprises next year. Additionally, enterprises will unlock more value from machine learning in allowing them to analyse complex datasets, identify patterns, and act with velocity. Streamlining laborious and manual tasks such as data modelling will allow enterprises to solve more challenges with greater speed, while scaling and enabling faster iteration and product evolution. Use cases will be more internally focused than GenAI, with interest coming from large IT organisations in companies such as banks and telcos with complex infrastructure environments. With machine learning and Agentic AI, seamless and rapid access to the right decision-making data becomes increasingly critical.
Enterprise spend on AI will rise dramatically in 2025; pivot towards grounded approaches such as RAG
Paradoxically, in dollar terms, enterprise investments in AI will increase in 2025 while the total number of GenAI proof of concepts (POCs) and pilots will decline. In 2024, the failure rate for POCs was higher than anticipated as they failed to deliver on expectations, or were not economically viable when scaling from the training phase to the inference phase.
Rather than an AI reckoning, enterprises will move toward a renewed focus on fundamental business values and practical AI. Generic, off-the-shelf AI solutions like ChatGPT are set to decline in enterprise use as trust concerns over output reliability increase. In 2025, organisations will increasingly pivot to grounded approaches leveraging techniques like Retrieval-Augmented Generation (RAG).
“Our mission is to empower enterprises to unlock the full potential of their data, driving meaningful and responsible AI adoption in 2025 and beyond.”
Ajeya Motaganahalli, VP – Engineering and MD – India R&D, Pure Storage
This shift will reflect a deeper commitment to AI transparency and ethics, with a preference for context-aware systems that mitigate data biases and inaccuracies. The demand for RAG will surge, particularly in fields like healthcare and financial services, where real-time data integration and contextually accurate responses are critical for nuanced understanding and decision-making.
The value of data will be thrust back into the spotlight in 2025 as organisations seek better outcomes from AI & Analytics investments
One of the key learnings from 2023/4 is that a less sophisticated algorithm powered by a large dataset will outperform a more sophisticated algorithm accessing a smaller dataset. Armed with this knowledge, enterprises in 2025 will undertake projects to free-up siloed and locked-up datasets in the quest to improve the output of their analytics and AI investments.
This emphasis on data unification will also reflect a broader understanding of data’s strategic importance in driving innovation and maintaining a competitive edge. As organisations aim to harness the full potential of AI and analytics, they will prioritise initiatives that enhance data quality, streamline access, and foster collaboration among teams. Ultimately, this focus on unifying internal datasets will pave the way for more informed decision-making, improved customer experiences, and sustainable growth.
Sustainability will return to the top 3 of corporate priorities as we approach the first milestone of 2030
2030 is a milestone that many companies set to meet sustainability targets–targets that have been put on the backburner due to AI FOMO of the past couple of years. Governments and regulatory organisations are intensifying efforts to mandate companies to meet their sustainability obligations. Enterprises will now have to prioritise energy-efficient technology solutions in order to meet those obligations.
Cybersecurity strategies shift to Data Protection
Cybersecurity strategies in 2025 will move towards data protection, as organisations come to terms with being attacked no longer a question of “if” but “when”. Several factors are driving this shift in strategy: cybercriminal capabilities being enhanced by AI; increased national legislation; and more stringent compliance requirements from regulatory authorities. When GenAI was first introduced, we saw how ChatGPT was used to improve the quality of phishing emails. Cybercriminals have become even more sophisticated today, using recursive AI to find vulnerabilities in their target’s IT infrastructure.
Organisations that fail to adapt to this AI-driven threat landscape risk severe financial losses, reputational damage, and potential business failure. Proactive investment in advanced cybersecurity measures and recovery strategies will be crucial for survival in the face of these evolving threats. Having a data protection strategy gives organisations a means of resuming business operations quickly in the event of an attack.
“As India continues its rapid digital transformation, 2025 will mark a pivotal year for organisations to embrace Industrial AI and advanced data-centric strategies. At Pure Storage, we are committed to helping businesses in India unlock the true value of their data while navigating challenges like AI governance, sustainability, and cybersecurity,” predicts Ramanujam Komanduri, Country Manager, Pure Storage India. “By providing innovative and energy-efficient solutions, we aim to empower enterprises to not only accelerate their AI journey but also drive impactful and sustainable outcomes.”
“Pure Storage India R&D is at the forefront of driving transformative innovation and empowering organisations to thrive in the evolving AI landscape. As businesses pivot towards Industrial AI, machine learning, and data-centric approaches, we are committed to delivering cutting-edge solutions that prioritise scalability, sustainability, and security. Our mission is to empower enterprises to unlock the full potential of their data, driving meaningful and responsible AI adoption in 2025 and beyond,” said Ajeya Motaganahalli, VP – Engineering and MD – India R&D, Pure Storage.
