Part 4 of the “The Secret Behind the Intelligent Enterprise” series
With great excitement in experimentation, hype, and investment, artificial intelligence (AI) is often discussed as the technological answer for every conceivable business problem. And some companies – from well-established enterprises to rising startups – will even throw around this term with tremendous ease and frequency to make products, services, and experiences appear cutting-edge and competitive.
The advancements often attributed to AI, though, are often sold on a conceptual level that has yet to be built or clearly defined. In most cases, AI innovations are nothing more than simple scenarios running on linear regression models that promise outcomes that surprise, connect, and engage customers and employees in seamless ways.
But don’t be fooled: AI is more than just a one-size-fits-all capability that runs on predefined data-driven rules. True AI innovation creates a logic that enables business systems to learn and refine their responses, even to the point of handling anomalies.
Experimenting with the vast potential of AI
We’ve all seen how AI enables new interaction experiences, but its real power goes even deeper. From automating repetitive, low-value tasks to illuminating previously undiscovered insights, the technology allows for use cases that scale on demand and exponentially – a dramatic improvement over the typically linear trajectory of today’s business processes.
Realizing the full potential of AI requires businesses to move away from a rules-based approach and towards automated resolution by leveraging predictive and prescriptive analytics. This approach can enable solution matching with fast, relevant answers to technical questions, conversational interfaces embedded in existing applications to provide on-demand support, and automated translation services for collaboration platforms.
The key to achieving such competitive advantages from every AI investment is optimizing technical operations and associated business processes, for example:
- Make enterprise data more accessible and meaningful: Encourage employees to evolve their processes and everyday work behaviors by augmenting business intelligence with customer, user experience, device, and Internet of Things (IoT) data. This strategic approach opens the door not only to new business models, but also to better, faster, and even automated processing and decision-making. For example, algorithms can be built with data-science tools to boost much-coveted operational transparency and insight.
- Increase the efficiency of managing a massive volume of data: Explore cloud platforms that can host more extensive and complex AI and machine learning models. Capabilities such as automated translation, natural language processing, chatbots, robotic behavior, and conversational AI for built-in support can fuel more-engaging user experiences by using IoT devices that collect a wide variety of data, even those captured through sight and sound.
- Revolutionize decision-making with a new spin on data analytics: Produce analytics in ways that go beyond traditional, cold ROI measures to enrich and amplify decision-making. For example, presenting data with a hyper-dimensional view helps uncover patterns and spot outliers that humans normally cannot see. Additionally, causal data and combinatorial thinking enable decision-makers to engage in counter-factual thinking.
Overcoming challenges, energizing intelligent innovation
AI innovation has long been equated with initiatives such as self-driving cars, life-saving medical therapies, improved consumer safety, sustainable consumption of natural resources, and highly responsive supply chains. But all these advancements are just the beginning of what we will see unfold in this new decade.
Now AI is maturing to the point where delivering predictable outcomes, improving efficiencies, and personalizing experiences are possible – no matter the business model and industry.
By understanding emerging challenges and risks, companies can take advantage of AI capabilities opportunistically. But more importantly, they can create an underlying system of technology and data lakes to exploit the ever-expanding potential of digitalization internally and in the global marketplace.
Check every week for new installments to our blog series “The Secret Behind the Intelligent Enterprise” to explore best practices for implementing the latest emerging technologies.