The transformative power of Artificial Intelligence (AI) is at a strategic inflection point moving beyond its consumer-focused origins, towards starting to realise its potential in an enterprise.
So far, AI has proven itself in supporting three important enterprise needs: automating business processes, gaining insight through data analysis, and engaging with customers and employees. While the combination of data, cloud, and AI provides enterprises a competitive advantage to digital initiatives, businesses want to discover greater value from AI, democratise it across their teams, and de-risk its application to be ethical, explainable, and responsible.
However, establishing return on investment on familiar trials of potential use cases and scaling beyond proof-of-concept has not fully convinced the C-suite about adopting AI.
To AI or not to AI?
Even as enterprises aim to vault their AI deployment over the functional-level bar and into other areas of their businesses, they face multiple challenges in leveraging the technology’s full potential. The technology itself is evolving at such a rapid pace that the CIOs have a tough time in deciding what works best for them. Besides, they need to deal with legacy technology systems and business processes, a dire shortage of talent and leveraging a complex ecosystem.
Even if they manage to get past all these potential barriers, there are challenges around governance, regulations, explainability, and trustworthiness of the technology. Not an enviable position to manage such overwhelming complexity, in the face of unknown returns.
Yet, the CIOs cannot afford to miss out the transformational potential of the ‘technology of our age’ as most organisations expect sizable AI effects on IT, business operations, supply chain management, and customer-facing activities in the foreseeable future.
Discovering the nuggets
Defining AI in the organisation in its current state would be a good start. This could involve a comprehensive assessment across the organisation of its AI maturity, a tech-enabled discovery process (including process discovery, data-based, outcome-based or asset-based discovery, discovery based on industry trends, etc.), measuring the value of different business cases where the technology can make an impact and drawing up a technology roadmap in parallel to an AI strategy.
The strategic roadmap itself can be defined through a value realisation framework that combines an assessment of:
Complexity — rating opportunities on implementation complexity
Value — use case cost and benefit driver’s assessment
Prioritisation of use cases pipeline to define roadmap for value realisation
Drawing up a technology roadmap
Plan to realise the value potential aligned with the strategic company vision for AI
Unleashing AI through democratisation
AI’s transformative potential lies in the fact that it can be applied across the enterprise — from HR to finance, marketing to legal, or strategy to sales. When it comes to enterprise IT, democratising AI means making intelligence accessible for every department, perhaps even for every person within the organisation. AI’s magic lies in the fact that the more data it is fed, the more it can be trained to deliver desired outcomes.
Unleashing AI beyond the confines of data scientists
A platform approach is the best possible way to achieve this objective. A full stack AI platform allows enterprises to leverage the best of open source and proprietary platform, future-proofing their technology investments. This modular approach, applicable to individual use cases that address different technology services, grants enterprises the agility to switch underlying APIs or even models, when necessary. The ability to switch is critical when it comes to creating and scaling innovation using multiple channels.
Applying AI across the enterprise doesn’t have to be a challenge. A growing portfolio of ready-to-use AI solutions can be quickly adapted to specific business needs. AI also helps enterprises uncover actionable insights from their data estates, open-source data, and curated data exchanges on the cloud to build new AI models and use cases. With today’s applied AI services, businesses can create custom solutions, orchestrating offerings from start-ups in the thriving partner ecosystem who provide intelligent automation, AI solutions, data solutions, and enterprise security.
Today’s AI solutions and services are endless. Enterprises can build their AI cloud, access open source AI software as a service on their hybrid cloud infrastructure, and harness edge AI capabilities. These can work in tandem with any hyperscale cloud provider’s services providing more choices and future-proofing investments.
The time for enterprise AI has come. It is up to them to take advantage of a range of cognitive automation services and platforms to meet their needs.