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Interdisciplinary Innovation is Essential for Digital Transformation
Innovation stems from a hunger to want to do things better. Innovation takes place in many forms – from a workout routine, designing a car, or transforming old business processes.
Knowledge Enhancement Through Augmentation of Information
When training machine learning models, data augmentation is a popular technique to enhance the performance of deep learning neural networks. The amount of data available plays a critical role in how accurately and quickly a training model can learn – this leads to more robust deep learning.
What Role Does Information Play in the Future of Work?
Information is arguably the most essential resource within a company. However, knowing where or how to look for it is often a challenge for the workforce.
It is Time to Approach Customer Engagement as a Flywheel
The coined term "purchase funnel" has been used as a basis for sales, customer outreach, and engagement for decades. The purchase funnel looks at the customer journey through a relatively narrow lens, making the flywheel a more innovative and successful approach to customer interaction.
Hyperautomation is Not Slowing Down
The world’s largest enterprises continue to invest in hyperautomation projects, and we may soon see a similar boom in mid-size organizations as well.
Achieving the Total Experience with Case Deflection
Companies invested in self-service technology that quickly direct customers to their solutions are a huge step ahead. The truth is, businesses are serving an impatient world. Whether the impatience is warranted or not, the customer has the right to better and faster resolutions.
Generative AI: What Is It and How Is It Used?
Generative AI uses machine learning algorithms to create new content from existing content such as audio, video, text, image files, or even code.
What to Consider for your Insight Engine Rollout: Validate the ROI Calculation
So, you identified the use case, defined the success criteria, did hands-on testing, and involved the users? The final part of the blog series on what to consider for your insight engine rollout will focus on validating the ROI calculation.
What to Consider for your Insight Engine Rollout: Involve the Users
This next step is often overlooked but is as critical as any. Hands-on testing with company data serves clear value but should high-level decision-makers in the C-Suite be the only ones involved?
What to Consider for your Insight Engine Rollout: Hands-on Testing with Company Data
Once a company identifies its use cases and defines its success criteria, it is critical to do hands-on testing of the product using actual company data. This is part three of the blog series on what to consider for your insight engine rollout.
What to Consider for your Insight Engine Rollout: Define the Success Criteria
In part one of "What to Consider for your Insight Engine Rollout," we covered the critical first step of identifying and determining the use case. In this piece, we discuss step two – Define the Success Criteria.
What to Consider for your Insight Engine Rollout: Identify the Use Case
The applications a business can use AI for are diverse, making virtually all sectors more efficient. Before integrating AI-powered technologies, such as an insight engine, the company management must ask the right questions and consider five critical points.