Artificial intelligence (AI) is playing an increasingly prevalent role in modern business, with 60% of IT leaders considering it a top priority for the future. More and more businesses are being pressured to “do something with AI” from their investors and the C-suite, but knowing how to get started can be tricky.
The answer to making AI success in a business can be found by introducing an AI System into your operations to optimize processes and leverage beneficial, prescriptive outputs from your existing data.
But what is an AI System? What is required to build an AI System? How exactly can AI help businesses? Let’s try and clear some of these things up…
What is AI in business?
In terms of AI’s role in a business setting, there are a number of ways that forward-thinking organizations are utilizing, and benefitting from, this exciting technology. Some of the most common applications of AI in business include the continued rise of customer service chatbots to deal with online questions and queries, as well as the growing usage of image recognition tools and software.
One area that is increasingly gaining traction is businesses using machine learning – a subset of AI – in order to gather more value from their data. Modern businesses, particularly those in consumer-facing industries such as retail, are producing larger and larger volumes of transactional data. This, coupled with the decreasing costs of computational power thanks to the cloud, means that the optimization of data with technology has become a much more viable and valuable option for businesses.
They’re using this ML-powered, enhanced view of their information to improve their processes, increase efficiencies, and to improve the experience of their customers. In order to do this successfully – in a way that doesn’t optimize one aspect of a business to the detriment of another – we believe that businesses need an AI System to act as a layer of intelligence that makes their existing systems smarter.
What is an AI System?
At Peak, we believe that we’re at the dawn of an exciting new era in modern technology; the AI era. Just like every business needs an ERP system or a CRM system, we believe that every business will need an AI system in order to remain competitive in the near future. This, in simple terms, allows businesses to gain a more holistic view of their data, wherever it’s from or whatever shape it’s in, and use this data to power predictive and prescriptive insights.
Peak’s AI System and its three core solutions focus on specific business functions, driving tangible outcomes and ROI tied to wider business objectives. For instance, this could be more optimized advertising spend, increased forecasting accuracy, or reduced logistics costs.
However, as well as being able to optimize and improve specific functions of a business in isolation, a key differentiator of the Peak AI System is its ability to act as a profit-driving intelligence layer across an entire business by connecting up these three core solutions.
This allows you to optimize all elements, functions, and existing business systems. We believe that a beneficial AI system should be able to leverage data from across the entire value chain, rather than from individual data silos like the majority of the out-of-the-box AI tools currently available on the market.
An AI System should be able to seamlessly integrate into all of your existing systems – whether that’s CRM, ERP, or finance systems, for example – whilst getting smarter and smarter over time. This allows you to deploy the technology across the entire business, without needing to rip and replace, and without any extensive integration headaches.
Let’s get under the hood of the Peak AI System and look at some of the key things we considered when building it…
By leveraging serverless architecture, the Peak AI System has been specifically designed and built for the handling of large volumes of data at huge scale. It’s an enterprise-grade software-as-a-service (SaaS) platform, which places a key focus on data security. It’s designed to handle datasets and solutions of any size, with inputs and outputs streamed in real time with always-on ML models that get smarter over time as they ingest and learn from more and more data. The more you feed the system, the better the results will be. You can find out more about the infrastructure in this blog by our CEO, Richard Potter.
Management of the full AI workflow
An AI System should offer the unique ability to enable businesses to productionize AI, end-to-end, in a single platform. This means handling the entire workflow, from the ingestion of raw data to a fully-deployed, AI-driven business solution integrated back into your existing systems. This new practice of applying DevOps techniques to build, manage and monitor multiple AI/ML workflows is called MLOps.
Once data has been ingested into the Peak AI System successfully – having been screened through our proprietary GDPR algorithm to anonymize any personally identifiable information (PII) – it’s then unified and transformed using a sophisticated suite of data management tools and techniques. From here, AI solutions are applied to solve specific business challenges, with the predictive and prescriptive outputs then provided via APIs for system integration, or exported directly from the AI System’s user-friendly dashboards.
A key requirement of any AI system should be the ability to manage and operationalize the AI solutions easily and efficiently. The Peak AI System, therefore, has been designed and built with UI and UX at front of mind, allowing end users to easily access and utilize the AI-driven outputs our solutions provide. Each solution can be controlled via an API, enabling the seamless integration with your existing business systems and without the usual headaches and teething problems. We’ve placed a key focus on building the Peak AI System to ensure that it integrates with – and generates value from – all systems, meaning there’s no need to rip and replace your existing systems when looking to introduce AI and ML into your operation.
TL;DR – here are our five steps to AI System success:
Input link: ingest data from your business systems
AI Infrastructure: store and unify data in our secure and scalable infrastructure
AI Studio: Configure AI solutions to meet your business’ needs, or build custom ones
Solutions: Activate individual Peak solutions – either standalone or interconnected
Output link: Send outputs directly into business systems using APIs