From DIY (DIY) to Get-It-Done (GID) with Generative AI-Driven AI Apps

With the release of openly accessible generative AI applications like chatGPT, the pace of technological evolution has accelerated to levels that few thought was possible just a few months ago. With the rapid progress of the generative AI movement and the growing public exposure and comfort with LLM, expectations of what technology can do for us today have multiplied. This technology tipping point ushers in a whole new world where getting things done with the help of AI will become commonplace. And not so long ago the do-it-yourself trend would sound outdated.

The corporate world is not far behind as we move from DIY to AI-powered GID in every aspect of life. The age of web/mobile apps is evolving into the age of AI apps. Not only are AI apps inherently smarter and more conversational by leveraging generative AI, but they also lead to higher levels of efficiency through higher levels of automation, making data and data difficult for humans to leverage. Leverage learning to drive better business outcomes. speed and scale. The next phase of enterprise transformation will bring AI to every application, every business process, and every employee, so you can achieve more than you ever thought possible.

By automating tasks, providing personalized assistance, providing expert-level guidance, seamlessly integrating with existing tools, understanding user context, and continuously improving its capabilities, AI can help users move away from DIY approaches. Allows migration to the GID approach. By leveraging AI technology, users can focus their energy on higher-value activities while relying on intelligent systems to complete tasks and reach their goals more efficiently and effectively.

A new kind of AI app:

– Leverage Generative AI/LLM to add more intelligence and deeper automation, leveraging machine learning and natural language, image and voice processing where appropriate.

– Engage users through human-like conversational interfaces, moving beyond traditional GUIs, while being fully aware of user and organizational context (role, location, time, past history, priorities, etc.) It has human-like conversational and logical reasoning capabilities.

– Drive business intelligence with real-time decision support from vast knowledge bases, using better algorithms to analyze large amounts of data and detect patterns to make better decisions, Leverage predictive analytics to anticipate future needs.

– Proactively automate and coordinate information and actions across the enterprise, learning from each human interaction and behavioral pattern to deliver personalized experiences

– Improves efficiency and accuracy in various areas. Automate complex tasks, reduce errors, and handle tedious or repetitive processes.

AI apps can personalize experiences, facilitate learning and development, enhance collaboration, automate tasks, enable feedback, recognize achievements, promote well-being, and optimize work-life balance. This can improve employee engagement. By effectively leveraging AI technology, organizations can create more engaged and motivated employees.

Consider, for example, the digitization of a procurement application in a large enterprise. Processes such as supplier/vendor onboarding and engagement, processes from PR to her PO, contract management, etc. are greatly improved by providing services through AI apps compared to traditional his web and mobile apps. It can be improved. Here are some examples.

• Automated supplier/vendor assessment and onboarding: AI apps can analyze vast amounts of supplier data, including past performance, certifications, and industry ratings, to automate the supplier assessment process. Leveraging automated workflows that integrate with existing systems of record to analyze and create documents can save procurement teams many folds of manual time and effort.
• Intelligent Procurement and Negotiation: AI apps assist the procurement decision and negotiation process. By considering a variety of factors such as supplier capabilities, pricing models and contract terms, the app can provide intelligent recommendations on sourcing options. It also helps us propose negotiation strategies, analyze supplier proposals and optimize contract terms to achieve favorable results.
• Real-time supplier performance monitoring: AI apps can monitor supplier performance in real-time by analyzing data from various sources such as delivery dates, quality metrics, and customer feedback. It identifies potential issues and deviations from expected performance levels and provides alerts and corrective action recommendations. This ensures that suppliers meet agreed service levels and quality standards.
• Contract management and compliance: AI apps can automate contract management processes such as contract creation, tracking, and compliance monitoring. Analyze contract terms, detect anomalies, and provide alerts on contract renewals and expirations. The app also helps identify potential compliance risks, such as non-compliance with regulatory or contractual obligations, and provides guidance on mitigating these risks.
• Data-driven decision-making: AI algorithms analyze large amounts of procurement data, market trends, and supplier performance indicators to provide insights for data-driven decision-making. The app can generate reports, dashboards, and visualizations that provide valuable information on spending patterns, cost-saving opportunities, supplier performance, and overall sourcing effectiveness. These insights empower procurement professionals to make informed decisions and drive continuous improvement.
• Demand forecasting and inventory management: AI algorithms analyze historical purchasing data, market trends, and external factors to provide accurate demand forecasts. The app can also automatically generate purchase orders based on expected demand, optimize inventory levels, and suggest reorder points. This prevents out-of-stock and overstock situations, leading to increased cost efficiency and better supply chain management.

AI apps drive improvements across procurement workflows, leading to increased efficiency, reduced costs, improved supplier relationships, and increased overall procurement efficiency.

Another example of an area where AI apps can have a big impact on an organization is human resources. A HR recruiting or onboarding app that integrates generative AI offers several distinct advantages over traditional apps.

Here are some of the ways generative AI integration can enhance your HR app.

• Automated Resume Screening: Generative AI analyzes resumes and applications to automatically identify relevant skills, experience, and qualifications. By training on large datasets, AI models can learn patterns and make accurate assessments, saving HR professionals a lot of time in the initial screening process.
• Personalized candidate recommendations: With generative AI, the app can provide personalized candidate recommendations based on job requirements and candidate profile. AI models can match candidate skills, experience, and preferences to job descriptions, helping HR professionals quickly identify the best candidates.
• Intelligent interview assistance: AI-powered apps assist HR professionals during interviews by suggesting relevant questions based on the candidate’s background and job function. AI models analyze candidate responses and provide interviewers with real-time insights and feedback to aid in the evaluation process.
• Automated onboarding documents: Generative AI can automate the creation and completion of new employee onboarding documents. AI apps can generate personalized offer letters, employment contracts, and other required documents based on predefined templates and relevant information. This streamlines the onboarding process and reduces manual paperwork.
• Personalized onboarding plans: Using generative AI, HR apps can create personalized onboarding plans for new hires. AI models can consider employee roles, backgrounds and skill gaps to generate customized onboarding roadmaps. This helps new hires get up to speed faster and transition smoothly into their role.
• Continuous learning and development: The app leverages generative AI to recommend personalized learning and development opportunities based on employee skills, career goals, and performance. AI models can analyze employee data and suggest relevant training programs, courses, and resources to foster ongoing learning and career growth.

These AI-driven capabilities streamline the hiring and onboarding process, improve decision-making, enhance the employee experience, and empower HR professionals to make more informed and effective decisions. can support

This new world of AI apps will enable organizations to become leaner, more efficient, and adapt to change more quickly. Retraining AI apps to adapt to new processes is much faster and less error-prone than retraining and reskilling human resources. Employees can focus on more strategic activities while AI helps them accomplish much of the more tactical work. The rate of technological change has changed so much that we can no longer rely on humans to do everything ourselves.

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