Despite their sophistication, enterprise AI and advanced analytics systems are not always a resounding success for many organisations, often under-utilised and falling short their promise.
IT leaders already working with AI and data analytics know from first-hand experience the role of hardware and in-built acceleration as a critical component in delivering high performance in this area. They are key drivers of efficiencies, scale, speed and seamless integration. They are also essential to automation and seal the link between the timely delivery of data insights and time to business value.
However, organisations too often find themselves struggling under the burden of managing the infrastructure powering their analytics solutions. Putting the focus on hardware can transform underperforming AI and analytics workflows to power advanced scalability, speed, and intelligence. It’s here cloud and IaaS providers can add the most value to investment in AI and data analytics.
A mixed report card for AI and data analytics
Organisations are seeking efficiencies and cost savings through automation and advanced insights, and the competitive advantage of getting this right. Yet Computing research has found that in many cases they don‘t find it all that easy to carry out AI and analytics tasks across their entire data and workflows for a variety of reasons.
Whether it’s a lack of a coherent view of data or siloed, even fragmented, data, their efforts to date have produced mixed results. The improved reporting and analysis isn’t always translating into increased sales or insights that improve the ability to find new business.
Advanced analytics are a long way from maturity operationally, but while they‘re under-utilised at present, organisational demand should catch up with the value placed on advanced AI and data analytics by IT decision makers and leaders.
Cloud service providers are missing a significant opportunity to show real organisational benefit and build the attendant client loyalty that would follow if they showed the tangible business benefits of advanced AI analytics capabilities.
This shortfall provides fertile ground to improve their offering with advanced analytics and capacity. To seize the opportunities the shortcomings present, infrastructure service providers, and those who utilise them, should look to the role of hardware in delivering platform-wide effective AI and analytics workloads.
Leaning in to the value of hardware investments
To answer these organisational challenges, hardware, both at the edge and in the cloud, is integral to intelligent, insightful AI and analytics programs – and building in AI accelerators …….
Source: https://www.computing.co.uk/analysis/4042721/industry-voice-ease-core-ai-advanced-analytics-success