Artificial Intelligence is once again making waves across the tech world. The combination of new approaches to understanding language – foundation models and the generative AI revolution – and powerful, GPU-based compute is driving step function improvements in our ability to process, understand and engage in natural language. Whether enterprises are leveraging these powerful technologies to process and understand unstructured documents or build conversational AI platforms that surface knowledge or execute transactions to users, businesses must devise a strategy that combines powerful AI with the capacity to understand their business domain and meet their requirements at scale.
Unlock the power of Natural Language AI with Watson
IBM Watson Assistant was one of products evaluated in the 2023 Gartner® Magic QuadrantTM for Enterprise Conversational AI Platforms (CAIP), a market defined by Gartner as ¨the enterprise conversational AI platform market for software platforms used to build, orchestrate, and maintain multiple use.¨
Among product features and customer feedback, this year IBM showcased the capabilities of our “low-code” conversational AI building capability called Actions. Actions makes it dramatically easier for technical and non-technical users to create conversational flows without having to worry about orchestration and unexpected turns in a conversation. This next generation of Watson Assistant also offers new templates businesses can use to get up to speed quickly based on their domain. Finally, we have also included new integrations and capabilities that enable integrations to be shared across multiple actions.
This is not the only recent announcement we have from Gartner in the Natural Language AI space. In December of 2022, Gartner® also recognized IBM as a Leader in the Gartner Magic QuadrantTM for Insight Engines. Insight engines apply relevancy methods to discover, analyze, describe and organize content and data. They enable the interactive and proactive delivery or synthesis of information to people, and data to machines, in the context of their respective business moments. We believe IBM Watson Discovery‘s Applications use case with extract & enrich data capability catering to specific business domains as a key competitive differentiator.
We want to take a moment to thank our partners and customers who inspire our teams to continue to deliver AI-powered solutions that can drive real business results across the enterprise.
AI adoption on the rise
According to the 2022 AI adoption Index, a study by the IBM Institute of Business Value, ¨global AI adoption rate grew steadily and now is 35%, a four-point increase from the year before.¨ While adoption is increasing, getting projects into production and applying AI to address enterprise-wide use cases remains challenging for most organizations. Barriers businesses face today include limited AI skills, lack of tools or platforms to develop models, data complexity, and difficulty integrating and scaling AI.
Key questions that clients need to ask themselves when implementing AI in their organization are:
Can the technology speak the language of your business?
Can it be easily integrated across systems?
Does it offer the ability to scale across the organization with trust and confidence?
Why does powerful Natural Language AI matter for businesses transformation?
Natural language processing (NLP) is a form of AI that’s being applied in a particularly large array of settings. To date, enterprises have looked to take advantage of foundation models in already-proven NLP use cases:
Customer Engagement: Customers today expect effortless and personalized experiences. Whether through chatbots or voice-powered virtual assistants, Natural Language AI enables businesses to communicate with customers in a more human-like manner, improving customer satisfaction and loyalty.
Employee Productivity: Natural Language AI can help automate manual and repetitive tasks, which drives efficiencies and frees up time and resources, enabling employees to focus on higher value tasks.
Workflow Optimization and Decision Support: Natural Language AI can help streamline workflows by providing quick and accurate insights, recommendations, and predictions. This can help support decision making, reduce errors, and improve overall productivity.
IBM integrates Watson-powered Natural Language AI foundation models and capabilities from IBM Research to deliver value to clients.
IBM has the technology, expertise, and experience to help businesses:
Understand customers and employees.
IBM Watson technology is designed for business users –We all know that no two situations, industries or people are the same. IBM Watson can help determine the true meaning of the interaction based on the context of the relationship with the customer or employee. The solution gives users the ability to them to realize value with less training and more focus on end results. Supervised, unsupervised and hybrid training approaches enable continuous learning and refinement over time.
Automate answers and insights.
IBM Watson technologies help integrate AI-powered experiences with the systems, processes, and people that run businesses without migrating your tech stack. It helps extract information and insights from existing text and other documents with Natural Language AI and Smart Document Understanding to accelerate and augment business decisions and processes.
Accelerate new experiences and processes.
Watson solutions are designed to help all professionals, whether they have technical backgrounds, work with powerful AI solutions. Using low code approaches, repeatable templates and easy to understand metrics, users can easily build and maintain powerful solutions without a heavy reliance on technical experts.
With these solutions and the deep technical expertise of professionals who have led more than 40,000 AI engagements, IBM and its partners can help businesses meet their unique customer and business needs.
While proud of what we’ve accomplished this year, we remain focused on delivering solutions that drive true innovation and real business results to our clients and partners worldwide.
GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally, and MAGIC QUADRANT is a registered trademark of Gartner, Inc. and/or its affiliates and are used herein with permission. All rights reserved.
Gartner does not endorse any vendor, product or service depicted in its research publications and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s Research & Advisory organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose. Gartner Magic Quadrant for Enterprise Conversational AI Platforms, Bern Elliot, Gabriele Rigon, March 6th 2023.
Gartner Magic Quadrant for Insight Engines, Stephen Emmott, Anthony Mullen, David Pidsley, Tim Nelms, 12 December 2022.
This graphic was published by Gartner, Inc. as part of a larger research document and should be evaluated in the context of the entire document. The Gartner document is available upon request from IBM.