GUEST OPINION: The debate is over. We know “hybrid cloud” is the right strategic choice for businesses over a “single cloud alternative” for several reasons: costs, performance, data security, regulatory compliance, and incompatibility of certain applications to run consistently within all environments.
While hybrid cloud has become the obvious choice today, up until now, we’ve seen many organisations fall victim to a “hybrid by default” approach, where they’ve adopted cloud in pockets as they pursued “quick wins,” resulting in inconsistencies and siloed environments that drive up complexity and costs. A lack of intentionality in hybrid architecture can lead to low ROI in cloud programs and difficulty aligning technology decisions to business priorities.
On the other hand, “hybrid by design” enables organisations to take an intentional approach to structuring their hybrid IT estate using a mix of public and private clouds, and on-premises data centres to achieve key business priorities and improve ROI by 3X.
At the core it’s all about purposefully building an architecture to drive business acceleration, step-change increase in developer productivity, improved infrastructure cost efficiency and strengthened security posture through standardised by design practices.
In fact, this year Australian businesses spent more than $23.3 billion on cloud services, an increase of 19.7% from 2023, according to Gartner.
The global survey also shows that cloud platforms continue to be a focus for ANZ CIOs, with 79% expecting to invest the second largest amount of technology funding on cloud platforms.
And now, generative AI has captured the attention of business leaders, making it clear that the values behind hybrid by design apply beyond cloud computing to the enterprise as a whole: platforms, security, AI, cloud, data—the entire technology estate.
Creating a generative-AI-ready tech foundation
When executing a generative AI strategy, organisations need to evaluate their current compute capacity, where data resides – in the cloud, on premises, at the edge, how data is accessed, necessary security controls, and how to use existing technology investments effectively.
To deliver model replication effectively across different environments and business workflows, and scale inferencing performance, organisations might want to consider using hybrid cloud platforms such as Red Hat Open Shift.
Certain generative AI uses cases need vast amounts of clean, accurate information to train models and generate effective outputs—which is what businesses need to fuel innovation. A robust data infrastructure with high-speed pipelines—is essential to feed the AI engine.
By investing in these modern tech stacks, you’re not just laying the groundwork for success. You’re building a foundation for continuous innovation, organisational agility with sound prioritisation frameworks, seamless data access and information exchange, serving as the foundation to create a perfect environment for generative AI. This translates to real results—a smarter way to work that drives profitable growth and efficient operations.
Business solutions: Hybrid by design
As organisations proceed on their AI journeys and deploy multiple uses cases in production across complex business workflows, they will need to leverage multiple AI models across various heterogeneous environments.
Hybrid cloud is the only viable choice to deliver these solutions and data integration costs effectively, and optimise model tuning, supported by the well-defined Enterprise AI Guardrails (explainability, transparency and ethics).
A hybrid by design approach can help to accelerate and scale the impact of data and generative AI across the business.
Scaled generative AI raises the bar
Given the wide range of enterprise use cases supported by generative AI (Customer Service Workflows, HR, Sales and Marketing, Operations, Finance, Supply Chain Transformation, Code Conversions and IT), organisations embracing generative AI can fundamentally drive meteoric improvement in business outcomes – as long as they embrace a hybrid by design approach.
We are seeing a massive uptick in AI platforms geared to help scale AI for business. For example IBM consultants use IBM Consulting Advantage and its purpose-built enterprise grade AI assets and assistants to helps clients rapidly accelerate generative AI use case realisation.
In addition, we are seeing an emergence of industry and domain aligned vision-language-action models and agents to accelerate generative AI adoption across enterprises.
Enterprises are also incorporating open architectures, open source model and open ecosystems (as opposed to proprietary options) as the foundation of their generative AI journey.
Finally, we expect business workflows and entire business ecosystems to be completely re-imagined with next generation generative AI, powered by industry and domain aligned vision-language-action models.
Organisations that embrace this innovation will likely be the winners of tomorrow – equipped with a strong foundation from which to compete in our AI-driven landscape.