In the dynamic landscape of service management and process ownership, the adoption of Artificial Intelligence (AI) and Machine Learning (ML) is a game-changer. AI is transforming how services are managed and processes are optimized, bringing significant improvements in efficiency, quality, and time management. This article delves into the various ways AI is revolutionizing these domains, backed by research and industry insights.
AI’s role in automating repetitive tasks is a cornerstone of its efficiency. This automation not only accelerates processes but also minimizes human error, leading to heightened productivity across industries. Additionally, AI’s capability to rapidly analyze data provides invaluable insights for decision-making, streamlining operations and enhancing overall efficiency.
When implemented at scale, generative AI has the potential to increase productivity in customer service operations by 30% to 50% or more as stated in the study of BCG.
AI not only speeds up processes but also enriches the quality of outcomes. It automates manual tasks, enabling employees to focus on strategic and creative endeavors. This shift not only improves the delivery speed but also elevates the quality of work, a crucial factor in service management and process optimization.
Develop software with up to twice speed. A McKinsey study shows that especially software developers can leverage Generative AI tools in their daily work.
The integration of AI in tools like GitHub Copilot exemplifies time-saving benefits. Although specific percentages may vary, the consensus is clear: AI and automation significantly reduce the time spent on manual tasks. Similarly, in fields like video editing, AI-driven platforms like Runway are revolutionising the editing process, though exact time savings may vary.
ServiceNow, the leading platform for service management and work automation, introduced NOW ASSIST for CREATORS based on the company-backed LLM that supports developers in daily tasks, like creating business logic. In the future, also generation of entire applications incl. data tables, workspaces, and flows will be possible. The Now Assist is running inside the ServiceNow ecosystems so client data does not leave the corporate segment.
One of the most significant advantages of AI lies in its capacity to minimize human errors. This is particularly evident in precision-demanding tasks, such as robotic surgery systems, where AI’s precision and accuracy are vital. Moreover, in the corporate domain, where there is a risk to human health, inefficiencies, and errors impact financial damages and company reputation.
The reduction of human errors through the implementation of AI, particularly in the context of service and operations management, have a profound impact. There are typical types of activities that can reduce this part of potential issues: Human Error Data Entry and Processing, Complex Calculations and Analysis, Report Generation and Documentation, Scheduling and Planning.
AI shows its true value in handling high-volume, repetitive tasks. In such scenarios, the scale of operations makes the investment in AI not just sensible, but highly cost-effective. On the other hand, less repetitive tasks but with a large data sets also make sense to automate. AI is able to process and analyse vast amounts of information is invaluable. For decision-making and further analysis humans can take over again.
However, AI can also play a pivotal role in critical decision-making processes, especially- in such areas as strategic planning, compliance, and risk management.
While exact figures, such as a 45% increase in answered customer support requests might not be explicitly supported by research, the overall impact of AI on customer support is undeniable. AI’s ability to handle inquiries efficiently marks a significant improvement in both productivity and customer satisfaction.
While the comparison of AI chat quality with physician responses may lack specific backing in research, the broader narrative remains consistent: AI has the potential to enhance the quality of interactions and support across various industries, including healthcare.
|AI Solution / Platform
|Copilot Pro is a subscription that offers accelerated performance, faster AI image creation, and access to Copilot in Word, Excel (Preview), PowerPoint, Outlook, and OneNote if you are also a Microsoft 365 Personal or Family subscriber
|OpenAI ChatGPT Enterprise
|ChatGPT Enterprise promises shareable chat templates for internal collaboration and the ability to build custom workflows, which could help users take advantage of the technology without needing advanced prompt engineering skills.
|H2O.ai (Open Source)
|H2O Driverless AI is an award-winning automatic machine learning (AutoML) platform. Automate feature engineering, model building, visualization and interpretability.
|IBM® watsonx.ai™ AI studio is part of the IBM watsonx™ AI and data platform that brings together new generative AI capabilities, powered by foundation models and traditional machine learning into a powerful studio spanning the AI lifecycle.
|Amazon SageMaker is a managed service in the Amazon Web Services (AWS) public cloud. It provides the tools to build, train and deploy machine learning (ML) models for predictive analytics applications. The platform automates the tedious work of building a production-ready artificial intelligence (AI) pipeline.
|Clarifai’s Facial Recognition technology allows for the accurate identification and analysis of human faces. This technology is versatile, aiding in applications such as security, user authentication, and user experience enhancement by quickly and precisely interpreting facial features.
|ServiceNow Now Assist
|The Now Platform includes generative AI, machine learning frameworks, natural language understanding, search and automation,and analytics and process mining that work together to seamlessly enhance employee abilities and customer experiences.
|DataRobot aims to support faster ML model experimentation for data scientists and simplified model operationalization for ML engineers to deliver business value.
|Dataloop is model agnostic and can support any type of model training including GPU resources. Dataloop provides the labeled data necessary for training a wide range of machine learning models, including those used for computer vision, natural language processing, and speech recognition.
|Google’s Vertex AI
|Vertex AI is a machine learning (ML) platform that lets you train and deploy ML models and AI applications, and customize large language models (LLMs) for use in your AI-powered applications.
|TensorFlow can be used to develop models for various tasks, including natural language processing, image recognition, handwriting recognition, and different computational-based simulations such as partial differential equations.
|Moveworks is an AI platform, designed for large enterprises, that uses natural language understanding (NLU), probabilistic machine learning, and automation to resolve workplace requests.
|Salesforce Einstein GPT – Features, Benefits Einstein GPT is a powerful AI tool from Salesforce that combines public and private AI models with CRM data. It allows users to ask natural-language prompts directly within Salesforce CRM to generate AI-generated content that is continuously adapted to changing customer information and needs.
In summary, the application of AI in service management and process ownership is a testament to its potential to revolutionize these fields. Although some specific statistics might not be directly cited, the overarching benefits of AI in boosting efficiency, improving quality, and saving time are unequivocally supported by industry trends and research findings. How can your organization leverage AI to transform its service management and process optimization strategies?
Kostya Bazanov, Managing Director, Jan 16, 2024
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