AI is the topic of the day. AI technologies are expanding into many areas of business and daily life. AI functions can be broadly categorized into various types, each designed to handle specific tasks or solve different problems. As a manager here are the twelve acronyms and AI functions you need to know.
- AI – Artificial Intelligence: The overarching term for machines or software that can perform tasks which typically require human intelligence; including learning, reasoning, and self-correction. AI examples you likely already use are systems for speech recognition on your phone or TV remote, spelling corrections in MS Office documents, and autofill functions in text applications.
- ML – Machine Learning: A subset of AI that involves the study and construction of algorithms that can learn from and make predictions or decisions based on data. Machine learning can be further divided into supervised learning (learning with labeled data), unsupervised learning (learning with unlabeled data to identify patterns), and reinforcement learning (learning based on actions and rewards).
- NLP – Natural Language Processing: A branch of AI that helps computers understand, interpret, and produce human language. This involves tasks like language translation, sentiment analysis, speech recognition, and chatbots. NLP is crucial for applications that require interaction with human language, from customer service automation to real-time communication tools. NLP analyzes customer feedback, reviews, and communications to derive insights about customer satisfaction and product performance.
- LLM – Large language models, like a GPT (Generative Pre-trained Transformer, yes that’s what it means), provide a broader understanding and generation capacity for human-like text. These models can generate coherent and contextually relevant responses based on a vast training dataset. One LLM use case is an e-commerce chatbot which uses an LLM to not only respond to customer queries about product availability, but also to make personalized product recommendations based on the customer’s browsing history and preferences.
- RPA – Robotic Process Automation: Technology that allows businesses to automate routine and repetitive tasks across applications and systems. RPA platforms can automate the tracking of inventory levels, order processing, and shipment tracking. This ensures efficient operations across the supply chain. RPA is also used in data entry, form filling, and automated customer service processes.
- OCR – Optical Character Recognition: Software that converts different types of documents, such as scanned paper documents, PDF files or images captured by a digital camera, into editable and searchable data. One use case is leveraging OCR technology to convert physical and digital invoices into editable formats, automating data entry and integration into accounting, claims and other systems. OCR is used to scan and digitize shipping labels and packing lists for faster and more accurate processing.
- CV – Computer Vision: An AI field that trains computers to interpret and understand the visual world. Applications include image recognition, video analysis, and different forms of surveillance. Computer vision is used extensively in quality control processes in manufacturing, facial recognition systems, and automated vehicle navigation. In mail and distribution, CV is used for tracking printing, insertion, parcel sorting, address verification, and detecting package conditions.
- ANN – Artificial Neural Networks: Algorithms inspired by the human brain that are used in machine learning and deep learning to process complex data inputs. ANNs model complex relationships between inputs and outputs in manufacturing processes, optimizing parameters for efficiency and quality. Useful in predictive maintenance for printing equipment and optimizing mail routing and sorting processes. Neural networks analyze images of products to identify defects that are subtle and typically hard for traditional vision systems to detect.
- DL – Deep Learning: A subset of ML that uses neural networks with many layers. Deep learning models monitor real-time data streams from machinery to identify anomalies that could indicate equipment problems or inefficiencies. Deep learning improves the accuracy of computer vision applications used in identifying product defects or guiding robots for picking and assembly tasks. Deep learning can enhance image recognition in printing operations, quality control, and even in optimizing package and shipment logistics.
- IoT – Internet of Things: Describes the growing category of devices that are embedded with sensors, software, and other technologies for the purpose of connecting and exchanging data with other devices and systems over the Internet. IoT includes technology for smart homes, smart appliances, voice-activated home assistants and health monitors. In print and mail, IoT can connect various devices for automated inventory management, tracking systems, and proactive maintenance.
- BI – Business Intelligence: Technologies, applications, and practices for the collection, integration, analysis, and presentation of business information. Managers can use BI tools to analyze operational data from print and mail operations to improve efficiency and reduce costs.
- Predictive Analytics: Using statistical algorithms and machine learning techniques, predictive analytics forecasts future events based on historical data. Predictive analytics tools and methods are commonly categorized under ML or BI. Predictive analytics is widely used in risk assessment, marketing strategies, and supply chain management to anticipate outcomes and trends.
Many organizations are implementing new AI tools and simultaneously defining governance around the use of AI. As organizations seek to create efficiencies and reduce costs, they also need to educate users and protect data security with governance policies. How are you embracing AI?
As you implement change, remember, “AI won’t replace humans, but humans who use AI will replace humans that don’t.” Karim Lakhani, a Harvard Business School professor.
Lois Ritarossi, CMC®, is the President of High Rock Strategies, a consulting firm focused on sales and marketing strategies, and business growth for firms in the print, mail and communication sectors. Lois brings her clients a cross functional skill set and strategic thinking with disciplines in business strategy, sales process, sales training, marketing, software implementation, inkjet transformation and workflow optimization. Lois has enabled clients to successfully launch new products and services with integrated sales and marketing strategies, and enabled sales teams to effectively win new business. You can reach Lois at https://www.highrockstrategies.com/ or Lritarossi@highrockstrategies.com