Mike Gualtieri

VP, Principal Analyst

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Spend On Generative AI Will Grow 36% Annually To 2030

Michael O'Grady September 11, 2023
Generative AI’s meteoric rise can be compared to the launch of social media, the smartphone, and the internet. The technology’s wide applicability across industries and occupations will drive massive growth, Forrester’s new forecast shows.
Blog

Watch Out For TuringBots: A New Generation Of Software Development

Diego Lo Giudice December 9, 2022
What are TuringBots? Hint: They will not replace you — not in the near future nor in the medium term. But they will augment your capabilities and make you look and work smarter.
Blog

Announcing The Forrester Wave™: AI/ML Platforms, Q3 2022

Rowan Curran July 12, 2022
Artificial intelligence applications are beginning to hit their stride, delivering end-to-end experiences for customers and employees that match or exceed human capacities. To help enterprises decide which AI/machine-learning (ML) platform to invest in, Forrester evaluated vendor platforms offered by Amazon Web Services, C3 AI, Cloudera, Databricks, Dataiku, DataRobot, Google, H2O.ai, IBM, Microsoft, Palantir, RapidMiner, RStudio, […]
Blog

Three Things To Know About The Forrester Wave™: AI Infrastructure, Q4 2021

Tracy Woo January 12, 2022
Investing in new AI infrastructure in 2022? My colleague Mike Gualtieri and I published a new Forrester Wave™ report: The Forrester Wave™: AI Infrastructure, Q4 2021. This is a brand-new topic for Forrester Wave evaluations. Its purpose is to dig into the massive explosion of AI that is quickly transforming enterprises. We looked at the […]
Blog

Prepare For AI That Learns To Code Your Enterprise Applications (Part 2)

Diego Lo Giudice July 8, 2021
The future of work for application development and delivery professionals will look very different. Learn how to prepare for it today.
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Prepare For AI That Learns To Code Your Enterprise Applications (Part 1)

Diego Lo Giudice March 18, 2021
Software Development, Past And Present Shortfalls As digital accelerates, so does the demand for business applications. And the complexity of building business applications is growing, despite all the innovations we’ve created during the past 20 years. Decision-makers have tried leveraging prepackaged business apps on-premises and now also in the cloud — only to find they […]
Blog

Sizing The AI Software Market: Not As Big As Investors Expect But Still $37 Billion By 2025

Andrew Bartels December 10, 2020
Forrester forecasts the AI software market will grow to $37 billion by 2025. Find out what's driving the growth and where the limitations are in this blog post.
Blog

AMD Acquires Xilinx To Bolster Its HPC Portfolio

Tracy Woo November 3, 2020
Last week, AMD entered into agreement to acquire chip manufacturer Xilinx through a $35 billion all-stock transaction. This is the latest gargantuan M&A deal in the semiconductor market to focus on new opportunities in processing, after the NVIDIA-Arm announcement. The AMD-Xilinx partnership is meant to broaden AMD’s product portfolio, which focuses on high-performance CPUs and […]
Blog

The 37 Major Machine-Learning Tools For 2020

Kjell Carlsson, Ph.D. May 27, 2020
Enterprises need more artificial intelligence and machine-learning (ML) solutions to drive value, transform their businesses, and outperform the competition. But firms find it challenging to navigate the lifecycle of developing, deploying, and maintaining their ML models and AI solutions. A key problem? They don’t have the right PAML (predictive analytics and machine learning) solutions that […]
Blog

Can AI Predict Global Pandemics Like The Coronavirus?

Mike Gualtieri March 23, 2020
AI is supposed to be the most powerful pattern detection and prediction technology in the world. It therefore begs the question: Can we use AI to predict future global pandemics far enough in advance to tamp them down or prevent them altogether?
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Who Are You, Citizen Data Scientist?

Mike Gualtieri February 8, 2019
Ugh. Everyone is talking about the citizen data scientist, but no one can define it (perhaps they know one when they see one). Here goes — the simplest definition of a citizen data scientist is: non-data scientist. That’s not a pejorative; it just means that citizen data scientists nobly desire to do data science but are […]
Blog

What Is Forrester’s Definition Of Enterprise AI?

Mike Gualtieri December 20, 2018
There are two types of AI. Watch the video below to learn which one you should forget about and which one you should go full steam ahead with. Have additional questions about enterprise AI? Schedule an inquiry to dive deeper, or check out my latest research here.
Blog

A Simple Solution To Machine-Learning Bias

Mike Gualtieri December 13, 2018
Machine-learning models may occasionally suggest an undesirable action. The action might be either biased or unethical — or just bad for business. Most of the time, the suggestion won’t be wrong. How can developers protect against these bad outcomes? It’s Simple You don’t have to do what the model tells you to do. If someone told […]
Blog

Let’s Make Data Dance At Forrester’s Data Strategy & Insights 2018 Forum

Mike Gualtieri November 7, 2018
Join us in Orlando on December 4, 2018 for Forrester’s first-ever Data Strategy & Insights 2018 Forum. We are super excited to bring you razor-sharp focus to the power of data, analytics, and machine learning. Back to dancing, because that is our conference theme — “Insights To Action: For Real This Time.” Data is too often […]
Blog

Predictions 2019: Business Insights Are A Many-Splendored Thing — Data Is Meant For More

Mike Gualtieri November 6, 2018
Enterprise Mindsets About Data Are Changing Give me a dashboard. Give me a report. Give me better insights. If that’s your approach, it’s old-school and you’re falling behind. Leading enterprises have shifted their data sensibilities to action-oriented insights. “Interesting” is no longer the standard for business insights efforts. Instead, insights projects must draw a straight […]
Blog

Read Two Forrester Waves™ On Machine Learning Solutions For Data Science Teams

Mike Gualtieri September 14, 2018
Machine learning is an elemental core competency. It is a fundamental building block to AI. It gives enterprises the power to predict. Most importantly, it can make enterprises gain the agility of disruptive upstarts by injecting scalable intelligence into customer experiences, business process applications, and employee decisions. That’s where predictive analytics and machine learning (PAML) solutions […]
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AI's Insatiable Appetite For Silicon Requires New Chips

Mike Gualtieri May 21, 2018
One breakthrough of AI is deep learning: a branch of machine learning that can uncannily identify objects in images, recognize voices, and create other predictive models by analyzing data. Deep learning can use regular CPUs, but for serious projects, data science and AI engineering teams must use AI chips such as GPUs that can handle […]
Blog

AI’s Insatiable Appetite For Silicon Requires New Chips

Mike Gualtieri May 21, 2018
One breakthrough of AI is deep learning: a branch of machine learning that can uncannily identify objects in images, recognize voices, and create other predictive models by analyzing data. Deep learning can use regular CPUs, but for serious projects, data science and AI engineering teams must use AI chips such as GPUs that can handle […]
Blog

Cognitive Search Is The AI Version Of Enterprise Search

Mike Gualtieri June 12, 2017
Written by Emily Miller, Senior Research Associate Stop Wasting Time More than half (54%) of global information workers are interrupted from their work a few times or more per month to spend time looking for or trying to get access to information, insights, and answers. The problem: Old keyword-based enterprise search engines of the past are obsolete. […]
Blog

Five Factors That Make Deep Learning Different – Go Deep Baby!

Mike Gualtieri May 16, 2017
At the highest conceptual level, deep learning is no different from supervised machine learning. Data scientists start with a labeled data set to train a model using an algorithm and, hopefully, end up with a model that is accurate enough at predicting the labels of new data that is run through the model. For example, […]
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