AI generativa versus AI predictiva: ¿cuál es la diferencia?​​​​​​​

La AI generativa y la AI predictiva tienen distintas diferencias y aplicaciones. Profundizaremos en las distinciones entre los dos y aprenderemos cómo se puede aprovechar cada uno para optimizar su nómina y sus operaciones comerciales.

Dueño de una cafetería que ejecuta la nómina en su teléfono móvil con la ayuda de AI
Autor Por the Roll Editorial Team el 23 de octubre de 2023
Tiempo de lectura Lectura: 4 min.

Chances are you’ve heard the famous quote “Time is money.” This saying has never been more true than in the modern-day business climate. We’ve all become accustomed to fast-paced lives where time is precious and efficiency reigns supreme.

The result? We’ve found ourselves increasingly reliant on emerging new technologies to simplify things and make lighter work of time-intensive tasks.

Enter artificial intelligence (AI). From the mundane duties that once occupied our days to more complex challenges that demand innovative solutions, AI and predictive analytics have become powerful assistants - and we're not just talking about the predictive text prompts on your smartphone!


Before we dig deeper into the fascinating world of artificial intelligence, it's essential to understand that not all AI is cut from the same cloth. Most notably, generative AI vs. predictive AI have distinct differences and applications. Join us as we delve into the distinctions between the two and learn how each can be harnessed to boost business efficiency and streamline your payroll operations.



What is Generative AI?


Generative AI is where imagination meets creation - the Picasso of the digital realm, if you will. With the ability to weave new stories, images, and sounds, generative artificial intelligence is all about creating fresh new content.

Unlike its predictive AI counterpart, which forecasts based on historical patterns, generative AI can assist writers, designers, and artists by offering previously unexplored creative possibilities. Yep, we're talking about infamous platforms like ChatGPT, Bard AI, Claude, and Socratic that have caused a huge buzz in the creative world.


Cómo funciona


Generative AI models learn by utilizing algorithms, deep learning, and neural networks to consume vast data sets and output new content that authentically replicates human-like creativity.

Sounds complex right? In reality, the technology is pretty straightforward. For example, AI models can study literature to mimic a particular style while adding an original twist. Likewise, they can produce new pieces of art in the manner of renowned painters, unique melodies in the style of music legends, and more.


Benefits of Generative AI


Generative AI isn't just for play, nor is it simple robotic automation. It's a complete game-changer for businesses and an innovative force with the power to reshape entire industries. This is perhaps one of the most significant distinctions when comparing artificial intelligence vs. predictive analytics. Por ejemplo:

  • In healthcare, generative AI can design molecules for potential drugs, revolutionizing discovery.
  • In design, generative models can whip up architectural plans that stretch conventional limits.
  • In gaming, generative gameplay can craft personalized adventures to ensure a unique and engaging narrative every time.


What is Predictive AI?


AI predictive analytics allow us to get a glimpse into tomorrow. While it can’t unveil the winning lottery numbers, it can take historical data and use it to identify trends so business owners and managers can make informed, data-driven decisions.

Predictive AI also has practical applications in everyday personal use. Let’s go back to our earlier example of predictive text. Artificial intelligence notes the commonly used words that follow others in your daily use to create personalized time-saving recommendations.


Cómo funciona


The key differentiator between generative AI vs. predictive analytics is, as the name would suggest, the analytical capabilities of predictive AI. Predictive models rely on machine learning algorithms to consume data. However, rather than use it to create new and novel content, predictive AI manipulates data sets to make accurate predictions and estimations about future events.



Benefits of Predictive AI  


Predictive AI has significant potential to help businesses streamline operations, anticipate market dynamics, and allocate resources more strategically. In fact, it has already been instrumental in facilitating change across various industries. Por ejemplo:

  • In sales, predictive AI can predict customer preferences and buying behaviors for new product launches.
  • In finance, AI predictive analytics are used to detect fraudulent transactions by flagging abnormal activity.
  • In inventory control, demand forecasting models utilize AI predictions to avoid stockouts and excess stock scenarios.


Generative AI vs. Predictive AI: Key Differences


It's difficult to compare generative AI vs. AI predictive models in a one-to-one way. That would be like comparing apples and oranges. Sure, they're both fruits - but in many ways, that's where the similarity ends because they have their own unique flavors and purposes. For example, you wouldn't make a pie using oranges or a mimosa with apple juice. It's the same with generative AI vs. predictive AI. Let's take a look at their key differences.





Some experts predict that as AI continues to develop, we'll see less of a distinction as new models emerge that seamlessly merge the two approaches. But for now, the pivotal distinctions between generative AI vs. predictive AI are:

  • Generative models create novel content, while predictive models shine in forecasting future trends based on existing data.
  • Generative AI focuses on imagination and creativity, whereas predictive AI focuses on strategic planning and risk mitigation.
  • Generative methodologies can spark innovation by generating entirely new concepts. Conversely, predictive processes reveal hidden patterns that already exist in data sets.



Both methodologies have their place. However, there are some limitations to relying solely on predictive analytics vs. AI models that can create entirely new concepts and content. Generative AI tools allow businesses to embrace innovation, save time, and make efficiencies across a range of business functions, including payroll operations. 


Generative AI-Driven Payroll from Roll by ADP

Roll’s powerful solutions are built upon the foundation that innovation should simplify business operations. Our AI-powered payroll solutions integrate cutting-edge technology that doesn’t just transform the way you pay your team — it changes the way your business thrives. Las funciones incluyen:

  • Automated payroll processing that swiftly calculates salaries, taxes, and deductions.
  • Predictive insights that allow you to address potential issues before they snowball into bigger problems.
  • Personalized employee experiences that enhance transparency and trust.
  • Improved operational efficiency thanks to reduced administrative overheads.
  • Accurate compliance in line with ever-evolving regulations drawn from ADP’s deep knowledge database.

Roll’s proprietary GenAI technology is based on a bespoke large language model (LLM). Our intelligent payroll app for small business makes running payroll a piece of cake. It’s so intuitive, you’ll swear you’ve used it before. Short story: if you know how to text, you know how to run payroll with Roll!

Ready to say goodbye to manual, time-consuming payroll and embrace the innovative, AI-driven future of payroll management? Sign up for your free trial today and get ready to Roll with ADP and the intuitive power of GenAI!

Chat-Based • Artificial Intelligence • Small Business Payroll • Small Business • Technology • Payroll
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