More and more companies are taking the artificial intelligence (AI) route to the cloud. This allows them to take advantage of the wide range of AI-base services available to drive insights from existing data.
AI can be thought of as the pinnacle of data comprehension and analysis, as a destination and a focused target for many organisations. AI does need quality and connected data and relies on data, integration and collaboration to achieve reliable and good quality outcomes. Within your organisation large amounts of data are already being produced, and by ensuring that the data is available, via connecting it to the cloud and integrating with existing back-end systems, an organisation is then prepared to optimise business processes, make more informed decisions, identify new revenue opportunities, and understand and predict customer behaviours in ways that were inconceivable only a few years ago.
AI offers the opportunity for a much wider and more thorough assessment of information and intelligence and thus the potential to significantly improve the quality of decision-making. Through AI, applications can analyse images, comprehend speech, interact in natural ways and make predictions using data.
- Allowing deeper dynamics customer engagement, with unlimited targeted end-user interactions, and at a vastly reduced cost.
- Providing real-time assistance to end-users, such as through chatbots, reducing the length of time users are held in a queue.
- Predicting outcomes, using analysis of existing data to identify patterns in customer demands for products and services.
- Delivering real time translation and voice to text services in applications.
Using cloud tools and frameworks to build, deploy and operationalise AI products and services at scale, Black Marble can harness intelligence with tooling such as Cognitive Services and Azure Machine Learning. In addition, using clearly defined organisational guidelines, we can endeavour to ensure that AIs are not only able to provide solid, reliable and beneficial outcomes, but are provable, auditable and , ultimately, accountable. This allows solutions to be created that reflect and reveal the ethical principles of the organisation to provide public trust in the use of AI.