HOW EDUCATORS ARE LEARNING TO USE A.I IN THE COLLEGE CLASSROOM

Yale University professor Alexander Gil Fuentes recently issued an unorthodox disclaimer on an assignment for his Introduction to Digital Humanities II course: “This final paper may be the strangest you’ve submitted for a grade in your whole life. You won’t be writing this one alone. You won’t be writing it with another person either — not directly in any case.”

Instead, students would be choosing a topic related to their current area of research and using ChatGPT to do the heavy lifting on the first draft. The students’ task would be to fact-check, correct, and enhance the AI’s suggestions. The completed project would need to include examples documenting the evolution from the initial AI-generated version to the final edited piece.

As technology continues to reshape traditional academic boundaries, Fuentes's initiative showcases the adaptive spirit of going with the flow of the tide instead of resisting it. Just two months after ChatGPT was released to the public, nearly one-third of college students admitted using the technology to assist with written homework. Close to 60% said they use it on more than half of their overall assignments. This trend underscores how important it is for educators to not only integrate generative AI into their teaching methods, but also to familiarize themselves with its capabilities firsthand.

ChatGPT isn’t the first technology to upend classroom dynamics — educators have long had love-hate relationships with tools like Wikipedia or even Spell Check. But much like calculators in the 1970s or the internet in the 1990s, generative AI “isn’t going back in the box,” says Jennifer Frederick, associate provost for academic initiatives at Yale. “We need to be graduating students who are adequately prepared,” says Frederick. 

Still, fewer than 10% of schools and universities have formal AI policies or guidance in place. This leaves instructors navigating a thorny landscape — one that’s as ripe with potential as it is riddled with question marks. 

Upending the status quo in academia

Fuentes is just one of many professors at Yale and higher-ed institutions across the country currently incorporating generative AI in the classroom — from creative writing and philosophy to computer science and even nursing. Aside from some of the obvious applications like essay writing, professors are using generative AI to help students with creative problem-solving, translation, coding, and research. Some features of generative AI platforms including advanced speech-to-text capabilities might even help neurodivergent learners or students with disabilities thrive.

Among educators, generative AI is evoking a mix of enthusiasm and trepidation. “A lot of the early headlines about AI in education were very alarmist: ‘The essay is dead, and students will never write anything again,’” says Frederick. “But we need a more holistic approach to thinking about AI than just through the lens of plagiarism.” 

Stephanie Atkins, teaching and learning center manager at Northern Wisconsin Technical College (NWTC), says the institution has taken a stance of cautious optimism. “Our approach has been, ‘Let’s get in and play. Let’s see how this technological advancement can help our students be successful,’” she says. 

One NWTC faculty member recently deployed AI in a legal issues class to help students brainstorm topics for their weekly papers. Others have used it for analysis and critical thinking exercises, framing the technology’s tendency to “hallucinate” (i.e., make things up) as a teachable moment by encouraging students to question and fact-check AI outputs. “In this capacity, students are moving from a rote knowledge base to an analysis and creation space, and that’s really where deep learning happens,” says Atkins.

A new teaching assistant

Educators are also using the technology to streamline the administrative parts of their own jobs. Karl Reischl, director of technology and information security at NWTC, noted he’s planning to use generative AI to come up with quizzes for an upcoming class he’s teaching on virtualization. “I can feed it all of my PowerPoints and other material I’m using in class and have it generate new quiz questions way faster than I could on my own,” he says. 

Additional possibilities include creating lesson plans, writing emails, and even role-playing through different educational scenarios. Atkins says this type of assistance can be a huge help for instructors unfamiliar with the ins and outs of academia. 

“We have faculty that come to us from industry, and do not always have a teaching background,” she says. “Generative AI helps them figure out where to start.”

Educating the educators

For educators looking to get their feet wet with AI, Reischl suggests hands-on experience. “The first step is just to use it, try it out, and learn different ways to ask it questions,” he says. For those looking for more in-depth reference material, there’s a slew of content available in the form of YouTube videos, articles, and online courses.

Tony Kashani, a professor of education at Antioch University who is currently writing two books on AI, suggests educators get more meta about it, asking ChatGPT — or other platforms like Google’s Bard — for advice on how to interact with them efficiently. Industry conferences can also be an incredibly useful resource.

Many universities are also developing their own content to help faculty navigate these murky waters. Yale’s Poorvu Center for Teaching and Learning, for example, leads workshops, faculty orientation discussions, panels and forums, and one-on-one consultations with instructors interested in dabbling in the technology for their courses and also for internal research and operations. NWTC produces webinars and compiles a newsletter full of AI resources. Atkins and her team also host formal professional development sessions that get educators experimenting with the tech.

With great power…

That said, there are still many areas of the technology that deserve a healthy dose of skepticism. One specific issue with AI is that it’s only as good as the data it’s trained on — and a lot of training data is biased, inaccurate, or fails to adequately take into account different cultural or linguistic intricacies. Because of this, Yale’s Frederick cautions against ascribing too much authority to AI outputs without independent verification. “They can be a good starting point for conversations about things like bias and representation and what’s missing and how to make that better,” she says.

There are also a number of ethical quagmires associated with the tech. How does the digital divide come into play, especially for students who don’t have access to generative AI in their K-12 years? Are researchers — or artists — whose work is used to train generative AI systems owed compensation? And how can educational institutions fight against mis- and disinformation perpetuated by these platforms?

…comes great responsibility

Kashani cautions it’s important to be upfront with students about the risks inherent in this powerful new technology, and equip them with the tools to use AI as a force for good. “If somebody is taking woodshop and you hand them an electric saw, you have to teach them the safety mechanisms first,” he says. “If we don’t teach kids how to use AI tools, they’re going to learn fast, and they’ll learn the wrong things.” 

Kashani notes that, for AI to have a net positive impact on higher education, that guidance needs to include helping students understand not only what AI can do, but what it can’t.  

“It can be an editorial assistant, or a tutor that’s available to you 24/7,” he says. “But it cannot replace you, as the person who is thinking, imagining, and has the ability to process information with a humanistic point of view."

 

SEO IS DEAD. LONG LIVE AO

I've been spending a lot of time with clients lately, discussing with them the mammoth changes coming to their businesses in the coming years. Invariably, the conversation centers on artificial intelligence, and invariably, I try to reframe their thinking.

Over the last few months, I've been spending time with Google's A.I.-first search engine. While it's clear the platform is still in beta, it's also clear to me that it's the future -- and companies better prepare.

If you haven't used it, Google's A.I.-based search represents a major change in how search results are displayed. Instead of simply showing results at the top of the page, Google A.I. search tries to answer your query, give you valuable context, allow you to ask follow-up questions, and otherwise provide useful results based on the A.I.'s interpretation of your search.

There's one more thing: While links to third-party sites are there, they're not nearly as apparent. Truth be told, I've found myself clicking on links far less often than I used to. Google's A.I. answers are that good. And if I don't need to go to another site, why should I?

All this is to say that the A.I. search of the future is here. And it will likely mean a drop in search traffic from Google as users, like me, opt to get their answers from Google's A.I. engine instead of heading to a website.

That, of course, creates a problem for companies that rely on search traffic. And it's precisely why I've told anyone who will listen that SEO in and of itself is dead. And now, if you're not changing your focus to algorithm optimization (AO), you're at serious risk of being left behind.

What Is AO? 

To be sure, SEO itself isn't dead. But investing substantial digital resources into optimizing your website to increase search traffic is dead.

The only way to be successful going forward at driving more digital traffic to your site is to invest time and resources into optimizing across algorithms. That means you will indeed need to have a website optimized for Google's algorithm, but more importantly, you'll need to optimize your content, calls to action, landing pages, and more to the algorithms that run our lives across Facebook, Instagram, and TikTok (special preference to Instagram and TikTok, by the way).

SEO was once nearly all that mattered in driving significant digital traffic to your website. Now, if you're not optimizing your digital marketing efforts for Instagram's Explore tab or TikTok's algorithm, you're in deep, deep trouble.

Yes, a Google search will continue to display search results to your website in the post-A.I. world, but if Google is going to provide answers to searchers without requiring them to click through to a website to get what they want, they'll have no need to come to your website. Your search traffic will decline and you'll need to figure out how to replenish that traffic somewhere else.

Enter AO.

The only way to rebuild your lost traffic will be to optimize your performance through algorithms. You'll need to become well-versed in Instagram and TikTok algorithms, and you'll need to be comfortable trying content concepts out -- and failing along the way.

Like it or not, algorithms impact our lives in an immeasurable number of ways. And now, they're going to take on an even greater importance in our businesses.

BY DON REISINGER, TECHNOLOGY AND BUSINESS WRITER@DONREISINGER

HOW TO SOLVE THE LEADERSHIP PARADOX

As a business coach for more than 25 years, I talk a lot about control and micromanagement. Because it really is one of the biggest problems in the business world and can hinder growth for years and years to come. But as a business leader, you may be asking yourself how do you find the right balance between effective leadership and micromanagement. Where is the line, and how do you make sure that you navigate appropriately? When is it too much?

Leadership often finds itself entangled in a paradox -- one that revolves around the elusive concept of control. So today, I want to delve into the intricacies of the leadership paradox and explore how effective leaders can navigate it by shifting their focus from control to influence.

Focus on the Right Things

At the heart of the leadership paradox lies the realization that control, in its traditional sense, is a mirage. Leaders who attempt to control every aspect of their domain often find themselves frustrated, exhausted, and ultimately less effective. Not to mention burnt out. The true essence of leadership lies not in controlling everything but in understanding what can be influenced and using that to your advantage.

Effective leaders recognize that there are external factors and variables beyond their control. Market trends, global events, and the actions of others are elements that cannot be dictated. And micromanagement won't change anything. However, they also understand that they possess a powerful tool -- the ability to influence outcomes.

By concentrating on influence, leaders can direct their energies towards areas where their expertise, vision, and guidance can make a difference. This shift in perspective allows for a more proactive approach to leadership, where the emphasis is on inspiring, guiding, and facilitating rather than attempting to micromanage every detail.

Some Examples

"So, David, what can I have 'control' of?" Here are a few examples of ways that you can have an influence and make a difference in your business.

• Who does the work? You can hire competent team members who have the skills, knowledge, and experience to do a good job.
• Who you should hand off tasks to.
• How you delegate tasks.
• How you follow up.
• How you allow for natural consequences when coaching or training.
• How you develop and train your staff.

This is the essence of being a good manager: picking the right people from the point of hire and onboarding them the right way. 

The leadership paradox beckons leaders to let go of the illusion of control and embrace the power of influence. By focusing on what they can influence, leaders become catalysts for change, innovation, and growth.

Effective leadership is not about holding the reins with an iron grip but about guiding the journey and inspiring the team towards a shared vision. It's a delicate dance between control and influence, and those who master this paradox find themselves at the helm of truly impactful and dynamic organizations. So, I want to encourage you to embrace the leadership paradox and unlock its full potential. 

BY DAVID FINKEL, CO-AUTHOR OF 'SCALE: SEVEN PROVEN PRINCIPLES TO GROW YOUR BUSINESS AND GET YOUR LIFE BACK'.@DAVIDFINKEL

A.I. COULD REPLACE CEOs---AND THEY KNOW IT

Artificial intelligence is transforming roles, from the entry level to the C-suite. But CEOs aren't just accepting this--they're embracing it.  

Forty-nine percent of CEOs believe that A.I. should automate or replace "most" or "all" of their job, according to a survey of over 500 CEOs from the online learning platform edX and the research firm Workplace Intelligence. This trumps the 20 percent of knowledge workers who believe the same, according to the survey.  

At first, this stark difference surprised Anant Agarwal, founder and former CEO of edX: "Frankly, the numbers almost seemed reversed to me." But he doesn't believe that there will be some mass exodus of CEOs; rather, he predicts a thorough transformation of the role--one in which CEOs could stand to gain if they are well-prepared.  

The CEO's job is composed of two parts, he says: the mundane and the exciting. Agarwal argues that A.I. tools will help replace the more mundane tasks to maximize the meaningful ones: creating sustainable revenue streams, introducing new products, inspiring employees, and more.  

This will be particularly helpful for CEOs of smaller companies, Agarwal says: "Small teams can begin looking much bigger, provided they're upskilled in the use of A.I. tools and technologies."  

The solution, therefore, is more learning and training, says Dan Schawbel, managing partner of Workplace Intelligence. "Executives who take steps to become proficient with A.I. will be better-equipped to make decisions that will position their companies for success in today's ever-evolving business landscape," he adds.

This competitive advantage is already clear to the C-suite--if a daunting premise. Seventy-nine percent of executives said they worry "if they don't learn how to use A.I., they'll be unprepared for the future of work," according to the survey. 

Their worries extend to the workforce, as well. According to the survey, CEOs and other C-suite executives believe that 49 percent of their workforce's skills will be irrelevant in 2025 and that 47 percent of their workforce is "unprepared for the future of work." Additionally, 87 percent say they're struggling to find candidates with A.I. skills. 

Some leaders have already taken steps to amend this: Forty-one percent increased their training budgets for A.I., and 39 percent are requiring their employees to learn A.I. skills. Looking forward, 72 percent of executives believe that their company should double down on A.I. learning and development programs over the next two years.  

Executives are also willing to sweeten the deal for skilled employees: Eighty-two percent believe A.I.-skilled workers should be paid more, and 74 percent believe they should be promoted more often. Even more, 82 percent of these C-suite executives believe that employees should be allowed to use A.I. to work multiple jobs.  

Still, there's room for improvement--and the issue is an urgent one: Thirty-nine percent of respondents say they'll likely quit their job within the next year for a position with stronger learning and development opportunities, according to the survey.  

"I see this as a massive opportunity for CEOs of small businesses," Agarwal says. "If they don't see the opportunity, but all the other CEOs do and jump on it and upskill their employees on this, they will lose." 

APPLE STARTED THE iPHONE 15 EVENT WITH AN UNEXPECTEDLY POWERFUL MASTER CLASS IN STORYTELLING

Apple, maybe more than any other company, has mastered the art of telling stories about how its products affect people's lives. It's become an essential part of the way it launches new products.

One of its favorite genres--if you will--involves the stories of how the Apple Watch has saved someone's life. Tim Cook has talked about how the company gets letters from people who were wearing an Apple Watch that notified them of an irregular heartbeat, for example. 

On Tuesday, during its iPhone 15 launch, the company started the event with a four-minute film called "Another Birthday." The film features eight people, including a mother and her unborn daughter, who celebrated another birthday because their lives were saved by a feature on an Apple device. 

It starts with a series of shots of individuals getting text messages on their iPhone or Apple Watch, wishing them happy birthday. As the film continues, we learn that one woman was notified of a low heart rate, and received emergency surgery to have a pacemaker installed. There is also a man who was saved after suffering hypothermia when he was able to use the Emergency SOS Satellite feature on his iPhone that allows you to send messages via satellite even when you're outside of cell service. 

Another man was saved after he suffered a seizure, causing a car accident, and his iPhone automatically called 911 while he was unconscious. Then, there's the mother, whose Apple Watch warned her of a high heart rate, causing doctors to rush her to an emergency delivery--saving both her life and her daughter's.

It's incredibly effective. 

You can argue that this sort of marketing unfairly pulls at people's heartstrings, or is emotionally manipulative. That's fair, but the thing is, I think Apple genuinely believes that one of its best features is that its products really do save lives. 

It's not as though the company is saying "buy our stuff or you'll die if you use a Galaxy phone." I think Apple is saying, basically, "We think these features are core part of giving people peace of mind, and that experience is essential to our brand."

Also, Apple delivers. These aren't aspirational features that sound good on paper. They work, and as--as a result--real people are alive today who wouldn't be otherwise. If I were Apple, I'd want to talk about it too.

To be sure, it's a delicate balance, but it's one Apple is better at than anyone else. As someone who covers a lot of tech events, I've seen many companies try to connect with the human side of their products. Almost all of them fail. 

Most of the time, it's because they try too hard to manufacture a connection, or they just aren't as good at the art of storytelling. A lot of things have changed about the way tech companies introduce new products--especially since the pandemic--but I actually think you can draw a direct line from the way Apple tells stories back to one of Steve Jobs's most effective skills.

No one was better at the stagecraft involved in making an audience care about a product than Jobs. He had a way of using stories to explain how a product would affect their lives.

In one famous example, Jobs pulled the original MacBook Air out of an interoffice envelope to make the point that it was thin and light. Except what he really did was use something everyone could relate to as an object lesson in what was so great about the laptop he was holding in his hand.

The lesson here is obvious: Good storytelling is one most effective ways to connect your products to your customers. Humans resonate with stories. It's how they connect with the world around them, and it's how they understand the benefits of the things you make.

"This year they all celebrated a birthday they never thought they'd have," the film finishes. There's nothing more relatable than that. 

REGULATION FOR ARTIFICIAL INTELLIGENCE IS ON THE HORIZON

Congress is looking to ink artificial intelligence regulation in just months--and tech titans like Mark Zuckerberg, Bill Gates, and Elon Musk all support regulatory guardrails for A.I. 

"There's some chance--above zero--that A.I. will kill us all. I think it's low, but there's some chance," Musk said to reporters, following a closed-door discussion on the potential for regulating artificial intelligence. "The consequences of getting A.I. wrong are severe."

The titans of tech descended onto Capitol Hill Wednesday for the session, which was the first of nine similar discussions delving into hot-button issues involving A.I. like workforce implications, innovation, privacy, copyright, and more. Besides Musk, Zuckerberg, and Gates, OpenAI's Sam Altman, Nvidia Corporation co-founder Jensen Huang, and Google's Sundar Pichai were among the nearly two dozen tech executives in attendance. 

Most of the tech executives found consensus during the six-hour discussion: Yes, A.I. should be regulated considering the threat that it poses.

"I asked everyone in the room, does government need to play a role in regulating A.I.?" Senator Chuck Schumer (D-N.Y.) said during a press briefing. "Every single person raised their hand, even though they had diverse views."

One idea that gained some support: creating a new federal agency to oversee artificial intelligence. Musk likened it to having an A.I. referee.

Wednesday's forum also touched on ideas for helping the U.S. stay competitive against foreign nations. "Washington needed to be involved, partly on behalf of the American people but also so that we as a nation can set the standard for the rest of the world," Senator Michael Bennet (D-Colo.) told reporters.

In terms of how quickly legislation can hit, Schumer told reporters that it's sometime "in the general category of months."

Businesses--along with the rest of the world--find themselves walking a tightrope when it comes to A.I. adoption: Integrate A.I. fast to grow against the competition, but beware of the disruptive effects. A survey from the U.S. Chamber of Commerce released on Thursday shows how increased technology adoption directly spurs profits, sales, and overall employment. 

But the road to getting there is nuanced. Agreeing that A.I. needs to be regulated is one thing, but crafting bipartisan legislation that impacts companies is a far different matter. Striking a balance is the ultimate test: While large tech players agree there's a need for regulation, they argue that too much could stifle innovation. Of course, laws do not look to see if the company being regulated agrees with the regulation, just that it adheres to it.

While all 100 senators received the invite, about 60 showed up. And not everyone was praising the historic forum. Senator Josh Hawley (R-Mo.) dubbed it "the Big Tech cocktail party," while Elizabeth Warren (D-Mass.) criticized the meeting for not being publicly accessible.

Tech billionaires "want to shape regulation so that the current tech billionaires are the ones who continue to dominate and make money," Senator Warren said in an interview with NBC News. "They should not have a forum to do that, especially a closed-door forum."

On the other side of Capitol Hill, President Biden has been accepting voluntary commitments from companies like Nvidia, Adobe, OpenAI, Microsoft, and Google to abide by A.I. rules including watermarking A.I.-generated content. The White House has been working on an A.I. executive order, reports Reuters. 

HOW TO WORK WITH CHATGPT'S GAPS IN LOGIC AND LANGUAGE GENERATION

In the glitzy world of tech, OpenAI's ChatGPT is undoubtedly stealing the limelight. This A.I. dynamo boasts impressive feats in language generation. But while it might wow with its wordplay, it can sometimes feel like it's skimming the surface. 

A study by Harvard found that while ChatGPT can shine in certain contexts, it only answered 58.8 percent of the logic-based questions correctly, indicating a gap in its reasoning prowess. Whether a startup or an existing business, ChatGPT is often pitched as a superpower that will solve any and all problems. You need to know where it works and where it doesn't. For business leaders, understanding the strengths and limitations of tools like ChatGPT is paramount to crafting efficient and meaningful AI strategies. 

ChatGPT has its strengths -- capable of crafting sentences that'd make a wordsmith nod in approval. But understanding the intricate dance of logic and language? That's a different ballgame. It's not just about mimicking human-like responses. We want the machine to understand us -- to discern the nuances, the emotion, the intent. But does ChatGPT really bridge that gap? Or is it just another pretender in a long line of tech marvels? 

An Overview of Logic in ChatGPT 

Under the hood of ChatGPT's acclaimed language generation capabilities is the sophisticated transformer architecture optimized for sequential data processing. Through its attention mechanisms, the model captures the essence of language, understanding and generating contextually relevant sentences.

However, spinning words eloquently is one thing; weaving logic into them is another. For a model to truly resonate, it needs more than linguistic flair. It craves a blend of language and logic. So, while ChatGPT can craft sentences with panache, does it truly get the logic? 

Limitations of Logic in ChatGPT  

In the context of language generation, ChatGPT's design heavily leans on statistical patterns and learned associations, sidestepping explicit logical constructs. This bias is evident right from its pre-training stage, where the transformer-based neural network immerses itself in a vast sea of unlabeled text, honing general linguistic features and patterns.

Research unveils glaring challenges in GPT-4's reasoning faculty, characterized by internal inconsistencies and shortcomings in applying foundational reasoning techniques. The model, at times, grapples with elementary concepts pivotal to reasoning, manifesting in what can be termed as hallucinations. These aren't merely empirical but delve deeper, touching the very essence of logical properties universally applicable. 

While external tools like search engines and knowledge graphs might offer some remediation, the real challenge is ensuring the model's internal logical soundness, especially when faced with complex logical or mathematical problems.

Handling Ambiguity and Uncertainty 

Diving into the complexities of natural language, it becomes clear why computational models like ChatGPT sometimes get caught in a linguistic maze. Let's assume a phrase like bank -- is it a financial institution or a river's edge? The inherent imprecision in language means that myriad interpretations can sprout from a single term.

For ChatGPT, differentiating between these subtle nuances demands disambiguation, which goes beyond mere statistical associations. Hand ChatGPT a layered sentence like, "I saw a man with a telescope," and it might grapple with its true essence: Did you use a telescope, or did the man have it?

Challenges in ChatGPT Logic -- Language Integration vs. Cognitive A.I.

Integrating logic and language in ChatGPT brings its own set of intricacies. At the forefront are scalability and complexity. As we attempt to manage vast knowledge bases and intricate logical constructs, we grapple with computational dilemmas and performance trade-offs. There's a pressing need for A.I. to understand the ebb and flow of context within conversations. Static logic won't cut it; our systems require a context-aware, dynamic logical foundation to effectively generate language.

Cognitive A.I. introduces a fresh perspective on this integration. It seeks to establish a seamless integration of logic and language through several intricate techniques:

• Neural-Symbolic Learning: At its core, cognitive A.I. employs neural symbolic learning where symbolic representations (logic) are embedded within neural networks. This ensures the system can reason and make deductions, not just predict based on statistical patterns.
• Dynamic Knowledge Graphs: These graphs are continually updated with new information, allowing the A.I. to maintain context and recall relevant details, bridging the gap between stored knowledge and real-time conversation dynamics.
• Contextual Embeddings: Unlike static word embeddings, contextual ones capture the meaning of words based on surrounding text. This assists in understanding nuanced statements and adjusting logic accordingly.
• Continuous Learning Loops: Incorporating feedback mechanisms where the A.I. refines its logic based on past interactions and errors. This ongoing learning helps in sharpening the balance between rigid logic and flexible conversational understanding.

Don't Get Lost in the Hype

ChatGPT-like tools can be a great aid for writing, research, and coding as long as the user takes full ownership of validating the content generated by the tool.

For any kind of output that requires factual precision, human experts always need to be in the loop to validate and correct before releasing the content.

However, for areas that require contextual reasoning, such as customer service, employee self-service, and a personal coach, you need cognitive A.I.-based technologies that understand language, have short-term and long-term memory, and are capable of making logical decisions from human inputs.

Generative AI generates. Cognitive AI thinks. It's wise to evaluate your AI deployment and mull over the potential benefits of incorporating cognitive AI solutions where a nuanced understanding and reasoning are essential.

BY SRINI PAGIDYALA, CO-FOUNDER, AIGO.AI@SRINI_PA

REASONS TO TRY GENERATIVE A.I

Businesses are using ChatGPT to help with essential business processes - those that deal directly with customers, investors and other key stakeholders. In general, companies are taking the risk of using the technology for processes such as customer service, marketing, raising capital, and boosting operational efficiency. The reason? Chatbots are easy for staff to use and their benefits are compelling. 

Here are five reasons to use ChatGPT to make essential business processes more efficient with examples of how to achieve the benefits.

1. To answer customer service questions more efficiently.

Many businesses operate call centers near the limit of their capacity - contributing to high turnover. Business leaders need ways to improve the productivity of their customer service staff and make their jobs more interesting.

ChatGPT enables businesses to achieve better customer service. According to Tech.co, Parker Heyn, digital marketing firm Parker Marker's CEO, used the chatbot to manage customer service inquiries and track customer data - cutting the digital marketer's processing time, saving the company money, and increasing the accuracy of its responses to customer questions.

2. To produce and distribute better marketing content faster.

With the proliferation of social media, the demands on marketing are more intense than ever. To get the attention of twitchy customers, companies need a steady stream of marketing compelling content.

Companies are using ChatGPT to draft and distribute marketing copy. Lauren Van Woerden, a content specialist using Ollo Metrics, eliminated writer's block and slashed copywriting time 30 percent to 40 percent by using clear, specific ChatGPT prompts, Tech.io reported. 

Alice Wu of Mind Meld PR used ChatGPT to tailor content for social media, blogs, and emails. Before sending out marketing content, she checked what ChatGPT produced to ensure Mind Meld's marketing message accurately conveyed what a product could deliver without controversial content, noted Tech.io. 

3. To make more efficient use of operational resources.

Many startups are having trouble raising new capital because venture capital firms are reluctant to commit more capital until the market for initial public offerings revive and give them a chance to earn a return on their investments. To get more done with their existing capital, companies are seeking to make their operations more efficient.

To that end, they use ChatGPT to identify best practices in automation, outsourcing, and supply chain management. According to Forbes, companies do that by using a prompt along the following lines: "How can I optimize my business operations, which involve [describe your business processes and how you make money] and increase efficiency, specifically in the areas of [describe the business areas where you suspect efficiency can be made]?"

4. To raise private capital.

Despite making capital last longer, business leaders may still need to brave the frozen venture capital market to raise more. To boost their odds of success, companies are using Generative AI.

ChatGPT helps private company CEOs to identify appropriate capital providers and to develop a pitch, set a valuation, and negotiate a final deal, Forbes reported. To that end, CEOs used a ChatGPT prompt along the following lines: "What are the key factors to consider when raising capital for my startup? My business does [describe what your business does] for the benefit of [describe your target audience]. Can you give me potential sources of funding and suggest how I approach each one?" 

5. To expand into new markets. 

To sustain a company's growth, business leaders must expand into new markets. Investors' eagerness to provide capital only to companies growing fast enough to sprint to liquidity heightens the pressure for companies to attack new markets.'

To help with that, companies use ChatGPT to identify new areas of market research, product diversification, international expansion, and partnerships. Forbes advises business leaders to prompt ChatGPT as follows: How can I scale my business and expand into new markets? My business is [describe your business] and most of our customers come from [describe how you get your clients]. We want ideas of new ways forward, potentially including new customer bases, product lines and partnerships. Please suggest some in order of priority."

Most businesses could use help in these areas - particularly those that rely on private capital. ChatGPT can help get them where they need to go.