As the cloud evolves, AI plays an important role in automating processes and speeding up digital transformation. It drives business value for enterprises by eliciting information from processes and refines the customer approach with customised solutions.
Using AI-based analytics, information can be traced, understood and interpreted quickly and accurately – converted into actionable insight that drives decision-making. A holistic approach that addresses the needs of all stakeholders (customers, investors, SMEs, employees, partners and vendors) involved is necessary when considering AI platforms.
You should consider the following 5 business drivers before on-boarding AI technologies into your organisation’s IT estate.
1. Customer Experience
AI-driven chat bots are gaining prominence for improving customer service in practically every consumer focussed industry. However, the power of AI lies in its ability to apply machine learning to understand behaviour and preferences of each customer, and personalise the experience for them. This is possible using bots and conversational user interfaces.
2. Customer Sentiment
AI can be used to analyse social media communication such as tweets, comments, reviews and complaints. It will enable enterprises to understand the tone and intent in conversations, derive sentiment analysis and undertake remedial action to course correct negative feedback.
3. Customer Verification
Biometric authentication using face and voice recognition are new ways to onboard customers. Verification is carried out through cognitive computing techniques.
4. Real-time Analytic-based Decisions
AI has the potential to reshape inventory management. It allows retailers to evaluate and store customer sentiment, combine logistics and supply chain trends with existing analytics around current buying behaviours.
In an increasingly omnichannel world, AI provides real time visibility into customer preferences across all touchpoints including store, online and mobile. As a result, retailers can tailor experiences and promotions to each specific channel.
5. Operational Efficiencies through Process Automation
Document classification and processing can be achieved in real time with AI. For instance, complex underwriting will be fast and accurate compared to manual checking processes that take several days to complete. AI can help with process mining by identifying bottlenecks and allocating resources, monitoring and improving SLAs and KPIs, and automating compliance check processes.
Cloud AI vs Premise-based technologies
While the choice of AI platform will be primarily driven by the broad level business drivers and scenarios described above, there are other technology level factors that can impact decision-making of the AI platform selection. Based on our experience, important factors to consider during selection include:
- Processing power for computation and image processing, as well as infrastructure scalability.
- Volume of information to be processed and stored.
- Distance to information and technology capability. Greater distance will necessitate higher network bandwidth between on premise systems and the cloud.
- Speed of response required.
- AI capability need based on business scenarios such as vision, speech, information search and catalogue, language or augmented reality.
- Organisation’s near term and long term objective, i.e. a quick experimentation versus strategic investment.
As part of our experience in providing technology driven digital transformation services to verticals such as public sector, healthcare, financial services and retail, we've identified cloud-based AI technologies offered by Microsoft, Amazon and Google as more promising compared to traditional, on premise AI technologies including open source platforms.
This is because cloud AI platforms offer an integrated set of technologies with a suite of capabilities. These help enterprises to deliver digital adoption and transformation at a rapid pace whilst offering the flexibility to make specific investments in AI-capabilities.