AI is both the present and the future, but how do we become leaders in its development and make it work for us? In this article, we explore the ecosystem your business needs to develop to capitalise on the benefits of AI. As generative AI and LLMs are enabling AI to move out of specific silos-of-use and create the beginning of truly enterprise-wide AI, now, more than ever, is the time to act.
The current landscape
Studies released this year have shown that 67% of organisations plan to increase their spending on technology and are prioritising investments in data and AI. If your company is data-driven, you could expect a revenue boost of between 10 and 15% versus competitors. The research also found that 98% of global executives think that AI foundational models will plan a key part in their business strategy over the next three to five years. More than ever, AI technology is being used across all industries as a central part of business. Those who are implementing AI today are likely to be the leaders of the future.
However, whilst we all realise that AI is likely to be the future, it’s becoming even more apparent that there’s a need to build the right foundations and broaden existing architecture to enable teams to scale their generative AI capabilities.
Bridging the data gap
Despite the overwhelming evidence of AI integration, it’s been widely communicated by consulting groups, Accenture, McKinsey and Deloitte that a mere 20% or fewer of companies excel at maximising the value from their data. This is despite investment, data strategies and hiring industry experts.
Business data should be driving better decision making, customer experience and response to market demands but companies are still struggling to use their data effectively and therefore struggling to maximise the benefits of their AI systems.
A report by MIT states that, “the generative AI era requires a data infrastructure that is flexible, scalable and efficient.” CIOs and technical leads must embrace the next generation of data infrastructures such as “data lakehouses”, which is a hybrid of a data warehouse and a data lake and can help “democratise access to data and analytics, enhance security and combine low-cost storage with high quality querying”.
Building a modern data platform should be the number one priority, but what else can we look to do to ready ourselves for the AI era?
- Cloud Migration – the cloud enables you to remove data landscape constraints, lower data management costs and dramatically increase value creation from previously inaccessible or redundant data.
- Scale AI and machine learning – build and scale your AI to solve problems, predict, decide and act in ways that transform business process.
- Reinvention through AI – innovate in a secure and structured way, designing proof of concepts quickly and cheaply to feed your innovation pipeline.
Realising the benefits
Once you’ve harnessed the power of data, leveraged the right tools and model sets for your business, here are some of the benefits you can expect to see:
- Speed and cost savings – clients that embrace AI benefit from phenomenal cost savings (over 40%), enjoy a speedier time to market (by 40%) and reduce processing time by over 70%.
- Experience and learning – industry experts are reporting a threefold increase in user satisfaction as well as a reported 30-50% reduction in the time to create new and meaningful use cases.
- Accelerated growth and innovation – speed up by 10 times your machine learning and AI proof of concepts whilst reducing failure rates and maximising performance.
Key watchouts
Is automation anxiety overblown?
Probably, but that doesn’t mean it should be ignored. The overriding consensus is that large-scale automation threats are not expected and AI will liberate the broader workforce allowing employees to focus on higher value and more interesting work.
What about commercial and societal risks?
CIOs must be mindful of the unique sets of governance required to avoid issues like copyright infringement, violations of IP, unreliable or unexplainable results and toxic content. Regulatory frameworks must be constantly monitored and adapted to the ever-changing technological landscape.
In conclusion, revisit your data strategy and discover what is working and what is not. Invest in technology, processes and governance and institutional structures to keep the guardrails in place. Do this and your business will reap the rewards of the AI revolution.
At The Siena Partnership, we work with our clients to help evolve their businesses and achieve transformation success.
If you’d like to continue the conversation with our consulting services expert, Rob Saunders, contact him here:
Robsaunders@wearesiena.com
www.linkedin.com/in/robnsaunders/