What is Explainable AI (XAI)?
Artificial Intelligence Or Machine Learning: What's Right For Your Business?
Cory McNeley is a Managing Director at UHY Consulting.
gettyArtificial intelligence (AI) has transformed the business landscape and changed how we work. Its capability to automate tasks, analyze extensive datasets efficiently and provide concise business insights facilitates both the speed and quality of business operations.
"Artificial intelligence" is often used to describe other technologies, such as machine learning (ML) and deep learning (DL). However, each of these technologies is distinct, and those differences impact which solution is right for your specific challenges. Understanding the high-level differences between each and the challenges that remain with implementation and adoption can help you have more meaningful and direct conversations about the role of these technologies in your organization.
Defining Artificial Intelligence And Machine LearningAI is centered on programs that replicate common human-like skills. AI can solve problems, perform advanced calculations, and make decisions through the use of statistical models, neural networks and programmed rules. AI is an umbrella term that also includes various subsets of technology like ML and DL.
ML allows programs to identify patterns from data, which is used to enhance the program's performance over time without the need for explicit programming. Common learning models include supervised, unsupervised and reinforcement learning techniques. This subset of AI is especially useful for data-driven decisions with extremely large data sets, such as sales forecasting. DL uses neural networks, a technique to replicate the human brain that is commonly found in image recognition and detection systems, as well as advanced AI applications such as autonomous vehicles.
Business Applications Of AI And MLThe world of communications, marketing and customer service is experiencing major disruption as a result of advancements in AI. Commercially available and custom-developed AI tools are helping companies provide high levels of customer service by employing advanced chatbots with more knowledge and flexibility than traditional chatbots. They can dissect and resolve complex inquiries without the need for human intervention. The natural language processing (NLP) aspect of modern AI allows these tools to provide customized marketing and communications that are reactive and continually evolving.
Common applications of ML technology include hyper-segmented customer profiling, predictive maintenance and fraud detection. Each of these is based on labeled (structured data), unlabeled (unstructured data) and reinforcement learning, where prior outputs are evaluated and used as inputs to adjust and refine ML's results.
Profiling customers based on previous purchasing habits, location, household income, etc., is nothing new, but combining this data with commuting route data, weather forecasts and social media activity could yield more valuable insight and recommendations.
In predictive maintenance, the mean time to failure by specific machine and physical location in the building—even down to floor orientation—along with machine models with common parts, operator assigned and forecasted demand help management address problems proactively and optimize scheduled downtime.
In fraud detection and prevention, customer profiling, institutional data, travel plans and social media help find potential fraud. Previously, major credit card processors used only a few dozen measures to predict fraud. Today, using ML, the number of parameters the card processor considers is far higher, likely reaching into the hundreds.
Challenges And Learning CurvesThere are challenges with implementing any of these technologies. Data quality ranks as the No. 1 issue. Similar to humans, bad information drives poorly informed decisions from AI. Businesses that plan on implementing any advanced AI tools need to review, catalog and cleanse their data to minimize potential issues with the tool.
Another major issue revolves around acquiring the right talent to work with these tools. According to the Bureau of Labor Statistics, data scientist jobs are projected to increase 36% from 2023 to 2033. With the high demand for expertise in this field, the difficulty in finding skilled and qualified talent to build and deploy could be increasingly difficult with the rising trends of adoption.
Several misconceptions about AI are also prevalent in organizations. While some solutions could be deemed plug-and-play, the vast majority require continual refinement and fine-tuning. This results in unrealistic expectations of what AI can and cannot do for your organization. Before you embark on your AI journey, clearly define your goals and objectives. Then, complete a detailed analysis to ensure the tool you are deploying will yield the expected results. Failed implementations could lead to cynical thinking about AI's capabilities.
ConclusionWhether AI or ML is right for your organization depends on context, and today's tools are advancing rapidly. At the core of the matter is data. These solutions need quality data to operate effectively. Is your organization ready?
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How AI Can Transform All Functions In Your Organization
Rena Fallstrom is the the Vice President of Communications at Glean.
gettyImplementing AI in the workplace is now a question of "when," not "if." AI tools are rapidly becoming more accessible and robust, though there is still a wide spectrum of acceptance and adoption.
A common misconception is that you need to be an engineer to use AI effectively. In reality, AI has the capacity to add value to every function of your organization. Here are three real-world examples of how to get the best ROI from AI applications across your organization.
Go-To-Market: Sales Pain PointsGetting a 360-degree view of customers throughout the sales cycle is increasingly challenging. Information is often distributed across multiple systems, making it time-consuming for your sales team to piece together recent interactions and next steps. This fragmentation leads to delays and disconnects in the sales process. For example, if one team member adds a note about a prospect in Slack that doesn't carry over to Salesforce, their colleague might fail to follow up in a timely manner.
AI Uses And OutcomesAI tools can automate manual processes and eliminate silos within the sales cycle, from lead outreach to contract negotiation. Your team can shorten sales cycles and accelerate time to revenue by consolidating information across documents and applications—ensuring that everyone has access to accurate, real-time data. New sales representatives can quickly get up to speed on their territory and accounts to engage with customers effectively from day one.
Instead of creating each customer communication from scratch, sales teams can leverage generative AI to craft messages that reflect your brand's tone and voice. This approach minimizes response times and gives employees more time to focus on improving the overall customer experience.
Research And Development: Engineering Pain PointsIn my experience working with engineering teams, engineers only spend part of their day actually coding. The rest of their time is dedicated to other tasks, including asking and answering questions within the team, searching for documentation, submitting and managing pull requests, discussing design decisions and planning for sprint work.
Teams rely heavily on collaboration, and there is a pressing need for better answer discovery processes within and across different engineering sub-teams (for example, DevOps and SRE engineers). Many teams also fall into the bad habit of allowing institutional knowledge to live solely in the heads of their most senior engineers. This creates bottlenecks and information gaps when other engineers are searching for answers to specific questions.
AI Uses And OutcomesAI helps engineering teams minimize hours spent on non-engineering tasks. By using AI tools, your engineers can instantly access company knowledge, technical documents and historical work to streamline all of their processes, from sprint planning to shipping final products.
When issues arise, team members can quickly debug and triage error codes by simultaneously searching dozens of platforms for the answers they need. These changes can significantly reduce the amount of time engineers spend looking for information, context-switching and answering repetitive questions, boosting their satisfaction and productivity and allowing them to focus on critical development work. Adopting AI tools in engineering often results in improved on-call issue resolution times and accelerated innovation and time to market.
General And Administrative: HR Pain PointsThe HR department is tasked with managing your organization's most valuable asset: your people. HR teams' responsibilities are extensive, including hiring new talent, supporting employee well-being and engagement, resolving conflicts and ensuring compliance with company policies and employment laws. It can be challenging for HR departments, especially those with limited resources, to keep current employees happy and engaged while also reducing biases and inefficiencies in recruitment and onboarding processes.
AI Uses And OutcomesAI acts as an effective force multiplier for your HR department, streamlining workflows and improving overall team efficiency. Employees can use AI tools to draft job descriptions, screen applications and reduce human bias in the hiring process. AI is capable of quickly analyzing and synthesizing large amounts of data, which your HR team can use in a wide range of applications, such as compiling interview feedback, writing performance review drafts and identifying patterns in employee satisfaction surveys. By implementing AI in their systems and processes, your HR department can expand its reach and improve its ability to proactively address potential issues.
AI's utility isn't limited to your engineering department. It has the power to transform all functions in your organization. To see where it can provide the most value, start by identifying the key pain points in a single department. Test AI tools to move the needle on one problem at a time, making adjustments, measuring progress and building on small wins as you go. With each improvement you make, you will expand your team's capabilities and your ultimate ROI.
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The AI-Savvy Leader
David De Cremer AI-Powered Learning as a Game Changer By Erin J. Kane
Erin Kane. PHOTO COURTESY OF DOUGLAS COUNTY, COLO., SCHOOL DISTRICT Most of us could not have imagined the speed at which artificial intelligence moved from being on the horizon to rapidly evolving and integrating into our web browsers, smartphones and Amazon searches.
As superintendent of a school system serving 62,000 students in more than 90 school sites, I decided we needed to embrace AI as quickly as possible. It takes some courage when you are the pioneer.
AI is transforming the workforce, and the AI initiatives we undertake will change the school experience and prepare students for their future. Our goal is to ensure we transform our systems as well, so our students will be prepared to lead and thrive.
Springboard ToolMy district, Douglas County School District in Colorado, developed a plan to use AI to prepare today's children for tomorrow's workforce. The use of AI is a cornerstone in our strategic planning process. It is also the focus of a new program being piloted by some of our schools.
This school year, we embarked on a pilot AI program in 18 of our schools. We partnered with Khanmigo — a tool created by Khan Academy designed for educators. Teachers serving students in grades 3-12 volunteered to try Khanmigo as a way to simplify workflows and assist students in the learning process. At the same time, Khanmigo is a perfect springboard for helping our principals, teachers, students and families alike in properly using AI for the school setting.
We are extremely optimistic that leveraging this AI-powered learning will be a game changer for all students, but particularly for English language learners and special education students.
Early in the pilot, we received an incredible e-mail from a speech-language pathologist and mother of a 6th grader in our district. She told us that many tears are shed when she tries to help her son, who has dyslexia, with math homework. One night, when her son pulled out his math book and the frustrations started, she suggested they log onto Khanmigo, and together they used the tool to learn the steps for multiplying decimals.
The mom stated: "There were NO tears, NO frustrations, and the best part was at the end of the math homework, my child was SO PROUD OF HIMSELF!!!! It was a miracle. Thank you so much for allowing schools to have this incredible tool."
Multiple PossibilitiesWe are so excited for what AI could potentially do for all students, including these uses:
Unparalleled student engagement. AI technologies allow us to create personalized lesson plans designed for the needs and interests of each individual student. Quadratics with superheroes? Done. Metaphors with a Taylor Swift theme? Easy.
Increased parent involvement via on-demand access to translation. We know that parent involvement is key to student success. AI platforms allow students and families to work together in their native language of choice. This removes the language barrier so that non-English-speaking families can still be engaged with their student's school work.
Tutoring and extra help available 24/7. In Douglas County, we provide each of our students with access to a technology device such as a laptop or Chromebook. AI programs are able to meet students at their ability level and are able to provide tutoring in any language.
Coaching advice. AI can be used to provide coaching advice such as financial aid options and career exploration to students and their families.
Alerts to teachers. If a student is falling behind or struggling in a particular subject, Khanmigo will alert the teacher so additional support can be provided.
The next decade will see more innovation, progress and wealth creation than we saw over the last century. It is more important than ever that we prepare our students, not only to adapt to that pace of change but to lead the change.
Erin Kane is superintendent of the Douglas County School District in Castle Rock, Colo.
Reskilling Cognitive Flexibility to Remake Your Brain By David L. ShrierCognitive flexibility is one of the building blocks of acquiring new knowledge and functioning effectively in a dynamic business ecosystem. It's an essential trait as the cadence of innovation accelerates and the need to be able to pick up new ideas and bring them into practice becomes even more urgent.
If you want to stay competitive in the age of AI, you need to retrain your brain so you can learn faster and bring that learning to bear in a context relevant to the workplace.
Sound impossible? It isn't. You need to begin by augmenting the human computer, your mind.
I have some good news for you: There are certain cognitive skills that you can develop that will help you in your everyday work and help you navigate and optimize how you work with artificial intelligence. Preparing your brain can help you prepare for the AI future.
I will suggest five principles for developing greater cognitive flexibility: (1) practice, (2) reflection, (3) sustained and gradual change, (4) peer learning, and (5) creative exploration.
Exploring Creatively[Two] of the best ways to learn are through peer education and creative exploration.
One of the benefits of peer learning is that if you are forced to explain a subject to someone else, you tend to understand it better yourself. You are required to reduce its principles to an explanation that someone else can absorb.
Children engage in creative exploration all the time. They do so solo, making up imaginary friends or scenarios. They do so in groups, collectively envisioning heroic settings or strange new worlds. Listening and talking to each other, they trade ideas back and forth, experimenting with concepts, throwing them away effortlessly, and trying out others as they endlessly create.
A famous creative collaboration known as the marshmallow challenge has been conducted globally with many different types of groups. In 18 minutes, with limited resources (a marshmallow, some string, tape and 20 pieces of uncooked spaghetti), competing teams work to build the tallest tower. It opens a fascinating window into problem solving and group dynamics.
Tom Wujec, a technologist who introduced the first computer graphic application to win an Academy Award, has a wonderful TED Talk explaining key insights of the marshmallow challenge that is worth reviewing. Some of his findings are these.
Five-year-olds are among the top performing groups. MBA and law students are among the worst-performing team configurations as they waste precious minutes navigating status and planning. They are searching for the one best answer rather than experimenting and discarding several ideas rapidly. Five-year-olds jump in, immediately trying out different configurations, with subtle social signaling as they grab pieces and interact with one another. And the children often produce the most interesting structures.
Group ContributionsThe most vibrant, scalable and repeatable innovations tend to come from creative collaborations, not solo genius. Diversity, as it turns out, is a necessary input to effective ideation. The more different perspectives you can introduce into a brainstorming discussion, the greater the likelihood you can fabricate creative collisions that produce truly breakthrough thinking.
Accordingly, when you need to solve a complex problem at work, think about whom you solve that problem with. Perhaps you can opinion shop ideas with a variety of colleagues rather than simply attempting to resolve the issue alone.
David Shrier is professor of practice of AI and innovation with Imperial College Business School in London and a visiting scholar with the Massachusetts Institute of Technology in Boston, Mass. This article is adapted from his book Welcome to AI: A Human Guide to Artificial Intelligence (Harvard Business Review Press, 2024) with permission of the publisher.
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