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AI Chatbots: An Increasingly Agile & Empathetic Path to Customer Engagement

4 months ago

Originally published June 2019. Updated July 2024 If the customer is always right, and the customer experience journey continues to increase in complexity, finding the best ways to serve individuals at scale—well, that just gets more challenging by the day. Can we find a solution in AI chatbots? Digital product designers are at the forefront of this challenge, working to translate cutting-edge AI capabilities into tangible benefits for real users. While we constantly seek the next big innovation, we also evaluate its potential to improve the customer experience. In the larger AI ecosystem, the brand-forward chatbot has an emerging story and a potentially exciting future. Once viewed as simple customer service tools, chatbots powered by AI are increasingly seen as powerful communication tools in their own right. Intelligent Customer Engagement Businesses, organizations, and governments are shifting their approach to user interaction in tandem with technological advancements. Chatbots are no longer just about answering FAQs. They’re becoming the frontline of personalized customer experiences, sales, and product development. Semrush reports the following AI statistics: 80% of marketers had chatbots in their customer experience strategy. 40% of businesses reported customer experience as the top motivation for using AI. Chatbots responded to 85% of customer service interactions. These numbers indicate a significant shift towards AI-powered customer engagement. But how are different sectors leveraging this technology? As the adoption of AI chatbots grows, the vision for their future becomes increasingly important. Industry leaders are already contemplating how these tools will shape customer interactions. Government-Powered AI Chats The UK Government Digital Service has been experimenting with AI-powered chatbots for its GOV.UK Chat solution. CX Today reports that their findings show promise: 70% of respondents found the bot replies useful. 65% were satisfied with the overall experience. However, the bots were not immune to hallucination, where the system provided incorrect information as fact. There’s potential for the technology to “have a major, and positive, impact,” Chris Bellamy, Director of GOV.UK shared in Inside GOV.UK. Bellamy writes: “The government has a duty to make sure it’s used responsibly, and this duty is one that we do not take lightly.” AI Insurance Correspondence For a growing number of doctors, AI chatbots—which can draft letters to insurers in seconds—are opening up a new front in the battle to approve costly claims, accomplishing in minutes what years of advocacy and attempts at healthcare reform have not. According to the New York Times, Dr. Tariq said Doximity GPT, a HIPAA-compliant chatbot version, had halved the time he spent on prior authorizations. Maybe more importantly, he said, the tool—which draws from his patient’s medical records and the insurer’s coverage requirements—has made his letters more successful. Since using AI to draft prior authorization requests, he said insurers have approved about 90% of his coverage requests, compared with about 10% before. Improving Empathy in Efficient Healthcare A study by New York University’s Grossman School of Medicine suggests that AI chatbots could “reduce the workload of care providers by enabling efficient and empathetic responses to patients’ concerns,“ according to lead study author William Small, MD. The same study revealed that generative AI responses outperformed human providers in terms of understandability and tone by 9.5%. Virtual Assistants for Banks—& More Bank of America’s Erica, an AI-powered virtual financial assistant, helps customers with various banking tasks and provides personalized financial advice. Bank of America reported that since its launch, the assistant has handled over 1 billion interactions, and more than 98% of clients get the answers they need using Erica. Wells Fargo’s assistant, Fargo, powered by Google’s AI, has also been a boon to the bank’s adoption of AI tech. Despite rigorous financial privacy regulations, according to VentureBeat, Wells Fargo has enrolled 4,000 employees in Stanford’s Human-centered AI program and is already executing “numerous” generative AI projects, focusing on enhancing back-office efficiency. By exploring these real-world applications, we can see how AI chatbots are indeed providing solutions for complex customer engagement at scale while also identifying areas for improvement and future development. Concerns & Mitigations AI chatbots offer promising solutions for customer engagement, but their implementation comes with risks. Recent examples highlight the need for careful consideration and robust safeguards. Cautionary Tale: NYC’s MyCity Chatbot Misstep CX Today reported that the Mayor of New York City was forced to defend the city’s “MyCity“ chatbot following a series of significant errors. Most notably, it advised some users to break the law by answering questions such as: “Do I have to accept tenants on rental assistance?“and: “Are buildings required to accept section 8 vouchers?“ with a definitive “no. “ The bot deduced that landlords are not mandated to accept these tenants. In New York City, it is unlawful for landlords to display prejudice based on the source of income, except in small buildings where the landlord or their family resides. ACCURACY & LEGAL IMPLICATIONS This incident underscores how AI chatbots can inadvertently provide incorrect or even illegal advice, potentially exposing organizations to legal risks. ETHICAL CONSIDERATIONS & PUBLIC TRUST Chatbots may reinforce biases or discriminatory practices if not properly designed and monitored. Errors like those in the NYC case can significantly damage public trust in government services and AI technologies. TECHNICAL NOTE: UNDERSTANDING CHATBOT INTELLIGENCE Modern AI chatbots often combine multiple technologies to provide more natural and effective interactions: Natural Language Processing (NLP): Helps chatbots understand user input by analyzing keywords and intent. Generative AI: Enables chatbots to create human-like responses through large language models (LLMs) that can adapt to conversation context. While some simpler chatbots (like basic FAQ or weather bots) might rely primarily on NLP, most advanced customer engagement solutions combine these and other AI techniques to provide more sophisticated, context-aware interactions. Is it too early for Gen AI with large language models where accuracy is crucial? Or should they begin with a predictable chatbot using NLP? This question highlights the ongoing debate about balancing innovation with reliability, especially in high-stakes environments like government services. Mitigating Risks AI chatbots can significantly improve efficiency, but responsible technologies are designed to augment human intelligence. The goal should be to allow customer service professionals to focus on more complex, high-value interactions requiring unique human skills such as empathy and nuanced problem-solving. To address these concerns, organizations implementing AI chatbots should: Conduct rigorous testing across a wide range of scenarios before public deployment. Implement ongoing monitoring through regular audits of chatbot responses. Provide clear disclaimers informing users of AI interaction and the potential need for verification. Establish human oversight, especially for sensitive topics. Ensure continuous learning by regularly updating the chatbot’s knowledge base. Addressing Bias in AI Chatbots Furthermore, because bias in AI chatbots can stem from various sources such as data, algorithms, and user interactions, a significant focus should be on effective mitigation strategies. Here are key approaches to address and prevent bias: Ensure data quality and diversity. Use diverse, high-quality data sets for training, actively including data from underrepresented groups. Implement algorithmic fairness. Employ techniques to identify and remove bias from the algorithms themselves. Maintain human oversight. Regularly monitor chatbot interactions to identify and address emerging biases. Promote transparency. Inform users they’re interacting with a chatbot and be clear about its limitations. Apply an empathy-driven approach. Keep the needs and experiences of end-users at the forefront of development. Conduct regular bias audits. Implement ongoing testing to identify and address potential biases in chatbot responses. Diversify development teams. Ensure your AI development team represents diverse perspectives and backgrounds. RESOURCES FOR DIGITAL EXECUTIVES AI Fairness 360 (AIF360) Toolkit: An open-source toolkit to help detect and mitigate bias. Google’s Responsible AI Practices: A guide for implementing AI responsibly. Microsoft’s Responsible AI Resources: Tools for developing AI systems ethically. The Ethics of AI Ethics: A research paper analyzing various AI ethics guidelines. IEEE’s Ethically Aligned Design: A guide for prioritizing ethics in AI systems. The Future of AI Chatbots: Transforming Customer Engagement On the horizon, AI chatbots are set to revolutionize business-customer connections even further. Some of these capabilities are already emerging, and their sophistication and widespread adoption are expected to increase. Enhanced Emotional Intelligence Current chatbots can detect basic sentiment, but future versions may be able to respond more nuancedly to complex emotional states, significantly improving customer satisfaction. Advanced Predictive Support Building on current predictive capabilities, future chatbots may anticipate customer needs with greater accuracy, potentially resolving issues before they arise. Seamless Omnichannel Integration Current chatbots operate across multiple channels, but future iterations will likely provide a more consistent experience across all customer touchpoints, from text to voice to visual interfaces. Hyper-Personalization Current chatbots offer some degree of personalization, but future versions may create experiences that feel uniquely tailored to each individual, even when serving millions of customers. Advancing Your Customer Engagement Strategy Thoughtful integration of AI chatbots into your customer engagement strategy has the potential to enhance customer satisfaction. When formulating a chatbot strategy, we recommend keeping these points in mind: Start with a clear vision of how chatbots align with your overall customer experience goals. Prioritize data quality and ethical considerations from the outset. Plan for continuous learning and improvement of your chatbot systems. Make sure to stay updated on new developments and be ready to adjust your approach. As Mark Zuckerberg aptly noted: “We think people want to interact with lots of different people and businesses, and there need to be a lot of different AIs that get created to reflect people’s different interests.“ We also envision an AI approach driven by empathy, where the needs and experiences of end-users stay at the forefront. We prioritize ethical considerations, transparency, and thorough testing to ensure positive and trustworthy customer interactions. The AI Chatbot Imperative: Embracing the Future of Customer Engagement The future of customer engagement is increasingly conversational, personalized, and AI-enhanced. Embracing new technology enables businesses to build better customer connections, drive efficiency, and fuel innovation with valuable insights. The path to AI-powered customer engagement may be complex. Still, the potential rewards—customer satisfaction, operational efficiency, and competitive advantage—may make it a journey worth taking. As you contemplate your AI chatbot strategy, ask yourself: How can AI chatbots not just meet but exceed your customers’ expectations? What unique value can your brand offer through this technology? Do you have the tools and partners to balance technical and user-centric design? The answers to these questions could define your competitive edge in the AI-driven future of customer engagement.

AI Chatbots: An Increasingly Agile & Empathetic Path to Customer Engagement Image

Originally published June 2019. Updated July 2024

If the customer is always right, and the customer experience journey continues to increase in complexity, finding the best ways to serve individuals at scale—well, that just gets more challenging by the day.

Can we find a solution in AI chatbots?

Digital product designers are at the forefront of this challenge, working to translate cutting-edge AI capabilities into tangible benefits for real users. While we constantly seek the next big innovation, we also evaluate its potential to improve the customer experience.

In the larger AI ecosystem, the brand-forward chatbot has an emerging story and a potentially exciting future. Once viewed as simple customer service tools, chatbots powered by AI are increasingly seen as powerful communication tools in their own right.

Intelligent Customer Engagement

Businesses, organizations, and governments are shifting their approach to user interaction in tandem with technological advancements. Chatbots are no longer just about answering FAQs. They’re becoming the frontline of personalized customer experiences, sales, and product development.

Semrush reports the following AI statistics:

80% of marketers had chatbots in their customer experience strategy.
40% of businesses reported customer experience as the top motivation for using AI.
Chatbots responded to 85% of customer service interactions.

These numbers indicate a significant shift towards AI-powered customer engagement. But how are different sectors leveraging this technology?

As the adoption of AI chatbots grows, the vision for their future becomes increasingly important. Industry leaders are already contemplating how these tools will shape customer interactions.

Government-Powered AI Chats

The UK Government Digital Service has been experimenting with AI-powered chatbots for its GOV.UK Chat solution. CX Today reports that their findings show promise:

70% of respondents found the bot replies useful.
65% were satisfied with the overall experience.

However, the bots were not immune to hallucination, where the system provided incorrect information as fact. There’s potential for the technology to “have a major, and positive, impact,” Chris Bellamy, Director of GOV.UK shared in Inside GOV.UK. Bellamy writes:

“The government has a duty to make sure it’s used responsibly, and this duty is one that we do not take lightly.”

AI Insurance Correspondence

For a growing number of doctors, AI chatbots—which can draft letters to insurers in seconds—are opening up a new front in the battle to approve costly claims, accomplishing in minutes what years of advocacy and attempts at healthcare reform have not.

According to the New York Times, Dr. Tariq said Doximity GPT, a HIPAA-compliant chatbot version, had halved the time he spent on prior authorizations. Maybe more importantly, he said, the tool—which draws from his patient’s medical records and the insurer’s coverage requirements—has made his letters more successful.

Since using AI to draft prior authorization requests, he said insurers have approved about 90% of his coverage requests, compared with about 10% before.

Improving Empathy in Efficient Healthcare

A study by New York University’s Grossman School of Medicine suggests that AI chatbots could “reduce the workload of care providers by enabling efficient and empathetic responses to patients’ concerns,“ according to lead study author William Small, MD.

The same study revealed that generative AI responses outperformed human providers in terms of understandability and tone by 9.5%.

Virtual Assistants for Banks—& More

Bank of America’s Erica, an AI-powered virtual financial assistant, helps customers with various banking tasks and provides personalized financial advice. Bank of America reported that since its launch, the assistant has handled over 1 billion interactions, and more than 98% of clients get the answers they need using Erica.

Wells Fargo’s assistant, Fargo, powered by Google’s AI, has also been a boon to the bank’s adoption of AI tech. Despite rigorous financial privacy regulations, according to VentureBeat, Wells Fargo has enrolled 4,000 employees in Stanford’s Human-centered AI program and is already executing “numerous” generative AI projects, focusing on enhancing back-office efficiency.

By exploring these real-world applications, we can see how AI chatbots are indeed providing solutions for complex customer engagement at scale while also identifying areas for improvement and future development.

Concerns & Mitigations

AI chatbots offer promising solutions for customer engagement, but their implementation comes with risks. Recent examples highlight the need for careful consideration and robust safeguards.

Cautionary Tale: NYC’s MyCity Chatbot Misstep

CX Today reported that the Mayor of New York City was forced to defend the city’s “MyCity“ chatbot following a series of significant errors. Most notably, it advised some users to break the law by answering questions such as: “Do I have to accept tenants on rental assistance?“and: “Are buildings required to accept section 8 vouchers?“ with a definitive “no. “

The bot deduced that landlords are not mandated to accept these tenants. In New York City, it is unlawful for landlords to display prejudice based on the source of income, except in small buildings where the landlord or their family resides.

Accuracy & Legal Implications

This incident underscores how AI chatbots can inadvertently provide incorrect or even illegal advice, potentially exposing organizations to legal risks.

Ethical Considerations & Public Trust

Chatbots may reinforce biases or discriminatory practices if not properly designed and monitored. Errors like those in the NYC case can significantly damage public trust in government services and AI technologies.

Technical Note: Understanding Chatbot Intelligence

Modern AI chatbots often combine multiple technologies to provide more natural and effective interactions:

Natural Language Processing (NLP): Helps chatbots understand user input by analyzing keywords and intent.
Generative AI: Enables chatbots to create human-like responses through large language models (LLMs) that can adapt to conversation context.

While some simpler chatbots (like basic FAQ or weather bots) might rely primarily on NLP, most advanced customer engagement solutions combine these and other AI techniques to provide more sophisticated, context-aware interactions.

Is it too early for Gen AI with large language models where accuracy is crucial? Or should they begin with a predictable chatbot using NLP? This question highlights the ongoing debate about balancing innovation with reliability, especially in high-stakes environments like government services.

Mitigating Risks

AI chatbots can significantly improve efficiency, but responsible technologies are designed to augment human intelligence. The goal should be to allow customer service professionals to focus on more complex, high-value interactions requiring unique human skills such as empathy and nuanced problem-solving.

To address these concerns, organizations implementing AI chatbots should:

Conduct rigorous testing across a wide range of scenarios before public deployment.
Implement ongoing monitoring through regular audits of chatbot responses.
Provide clear disclaimers informing users of AI interaction and the potential need for verification.
Establish human oversight, especially for sensitive topics.
Ensure continuous learning by regularly updating the chatbot’s knowledge base.

Addressing Bias in AI Chatbots

Furthermore, because bias in AI chatbots can stem from various sources such as data, algorithms, and user interactions, a significant focus should be on effective mitigation strategies. Here are key approaches to address and prevent bias:

Ensure data quality and diversity. Use diverse, high-quality data sets for training, actively including data from underrepresented groups.
Implement algorithmic fairness. Employ techniques to identify and remove bias from the algorithms themselves.
Maintain human oversight. Regularly monitor chatbot interactions to identify and address emerging biases.
Promote transparency. Inform users they’re interacting with a chatbot and be clear about its limitations.
Apply an empathy-driven approach. Keep the needs and experiences of end-users at the forefront of development.
Conduct regular bias audits. Implement ongoing testing to identify and address potential biases in chatbot responses.
Diversify development teams. Ensure your AI development team represents diverse perspectives and backgrounds.

Resources for Digital Executives

AI Fairness 360 (AIF360) Toolkit: An open-source toolkit to help detect and mitigate bias.
Google’s Responsible AI Practices: A guide for implementing AI responsibly.
Microsoft’s Responsible AI Resources: Tools for developing AI systems ethically.
The Ethics of AI Ethics: A research paper analyzing various AI ethics guidelines.
IEEE’s Ethically Aligned Design: A guide for prioritizing ethics in AI systems.

The Future of AI Chatbots: Transforming Customer Engagement

On the horizon, AI chatbots are set to revolutionize business-customer connections even further. Some of these capabilities are already emerging, and their sophistication and widespread adoption are expected to increase.

Enhanced Emotional Intelligence

Current chatbots can detect basic sentiment, but future versions may be able to respond more nuancedly to complex emotional states, significantly improving customer satisfaction.

Advanced Predictive Support

Building on current predictive capabilities, future chatbots may anticipate customer needs with greater accuracy, potentially resolving issues before they arise.

Seamless Omnichannel Integration

Current chatbots operate across multiple channels, but future iterations will likely provide a more consistent experience across all customer touchpoints, from text to voice to visual interfaces.

Hyper-Personalization

Current chatbots offer some degree of personalization, but future versions may create experiences that feel uniquely tailored to each individual, even when serving millions of customers.

Advancing Your Customer Engagement Strategy

Thoughtful integration of AI chatbots into your customer engagement strategy has the potential to enhance customer satisfaction. When formulating a chatbot strategy, we recommend keeping these points in mind:

Start with a clear vision of how chatbots align with your overall customer experience goals.
Prioritize data quality and ethical considerations from the outset.
Plan for continuous learning and improvement of your chatbot systems.
Make sure to stay updated on new developments and be ready to adjust your approach.

As Mark Zuckerberg aptly noted:

“We think people want to interact with lots of different people and businesses, and there need to be a lot of different AIs that get created to reflect people’s different interests.“

We also envision an AI approach driven by empathy, where the needs and experiences of end-users stay at the forefront. We prioritize ethical considerations, transparency, and thorough testing to ensure positive and trustworthy customer interactions.

The AI Chatbot Imperative: Embracing the Future of Customer Engagement

The future of customer engagement is increasingly conversational, personalized, and AI-enhanced. Embracing new technology enables businesses to build better customer connections, drive efficiency, and fuel innovation with valuable insights.

The path to AI-powered customer engagement may be complex. Still, the potential rewards—customer satisfaction, operational efficiency, and competitive advantage—may make it a journey worth taking.

As you contemplate your AI chatbot strategy, ask yourself:

How can AI chatbots not just meet but exceed your customers’ expectations?
What unique value can your brand offer through this technology?
Do you have the tools and partners to balance technical and user-centric design?

The answers to these questions could define your competitive edge in the AI-driven future of customer engagement.

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What is generative AI—and how does it impact businesses?

Generative AI is no longer just a futuristic concept but a reality set to revolutionize how businesses operate. It is a form of AI that can now quickly generate new content, images, and sounds.

Initially, large companies were afraid of generative AI applications like ChatGPT. Today, businesses seek guidance on the business implications of generative AI to understand the technology better and implement best practices within their organizations. The race is on to apply generative AI at scale, with just a few use cases, including:

Greater Personalization: Businesses can leverage generative AI technology to establish deeper customer connections through personalized content.
Enhanced Productivity: With AI assistance, employees can simplify tedious and repetitive tasks, freeing up their time for critical and creative tasks.
Content Production: Additionally, generative AI has the potential to transform the creative industry by producing a vast array of original content, from visuals to music.

Companies are finding ways to integrate generative AI capabilities into digital products, creating more targeted consumer solutions. But the journey from a spark of technology to full functionality isn’t straightforward. We’ve heard it straight from Brad Weber, InspiringApps CEO:

Our job as developers is to embed generative AI into other applications so that consumers benefit from it but don’t necessarily have to know the intricate details about how to work with it.

Developers now face the task of harnessing generative AI’s potential and integrating it into business solutions in meaningful yet user-friendly ways. We need to transform the opportunities generative AI presents into a fully functional car.

What is the relationship between generative AI and copyright law?

Tools such as ChatGPT have great potential for improving our lives. However, if not used correctly, they can also pose significant risks. Brad Weber explains:

There are lawsuits from copyright holders who say, “Hang on. Your model is fantastic, but it’s fantastic in part because you trained it on works that I generated—copyrighted works.”

While some argue that generative AI can create original content, others contend it can infringe on copyrighted works that may have trained its algorithms. With more artists and authors becoming increasingly litigious over the issue, it begs the question: how can we balance the benefits of generative AI with the need to respect intellectual property?

Tim Hayden from Brain+Trust applies a sage metaphor, quoting Willie Nelson’s emphasis on writing your own songs.

If we’re going to leverage AI for differentiated messaging, with the brand culture, with a customer-centric operation, then we don’t need to go to a third party and leverage a data set pulled from a bunch of public sources.

Corporations must be mindful of the outputs created by these tools and acknowledge any creative works produced by generative AI still fall under the jurisdiction of intellectual property laws. Companies using generative AI must be cautious of how the technology is used to create works that could infringe on existing copyrights.

What are some generative AI applications?

Generative AI has the potential to yield groundbreaking results. Being mindful of the potential legal pitfalls is just as important as leveraging the innovative capabilities of this advanced technology.

Integrating AI Assistants for Tailored Brand Experiences

Whether you are about to build a new app, maintain an existing one, or launch an app in the market for the first time, your digital product and brand must connect with customers to foster trust and create personalized experiences to engage them.

One of the most exciting and powerful potentials for generative AI is the creation of highly personalized customer experiences. By embracing generative AI on their terms, organizations can develop their brand personas and assistants, setting themselves apart and delivering unparalleled value to their customers.

With data being touted as a sacred asset, proprietary trainable models offer unparalleled protection and insight into customer journeys and relationships. Tim Hayden, CEO of Brain+Trust, predicts a surge in company-created brand personas through AI in the next 18 months, providing a personalized touch beyond what traditional apps offer. Harnessing AI to build brand-specific models will shape businesses’ futures.

Best Practices for Implementing Generative AI in Your Business

The key to generative AI success is understanding that it doesn’t replace human capabilities—it makes humans faster, wiser, and more efficient. Generative AI can assist businesses in scaling more rapidly than ever before. Here are a few best practices to make the most of AI for your business.

Use generative AI to differentiate your brand. Creating unique and tailored content helps businesses stay ahead of the competition, providing their audiences with a more personalized and engaging experience.
Use it to research and analyze your audience. Generative AI can identify patterns in customer behavior and generate personalized recommendations to increase engagement.
Use it to enhance decision-making. AI can analyze large amounts of information, helping to generate data-driven insights and forecasts to inform strategic planning and operational efficiency.
Data is key. Leverage your own proprietary data sets to train AI models, ensuring their relevance and accuracy for your specific business needs.
Human oversight remains crucial. Don’t rely solely on AI. Combine its capabilities with human judgment and expertise for optimal results.
Prioritize transparency and accountability. Understand how AI models reach their conclusions, mitigating potential biases and ensuring ethical usage.

Businesses can unlock a wealth of growth and innovation opportunities by strategically embracing generative AI.

What is the future of generative AI?

Generative AI has undeniably opened Pandora’s Box regarding copyright law, and the complexities are yet to be fully revealed. However, businesses in all industries should look ahead to this new technology with excitement.

Generative AI has already proven that it can revolutionize customer experiences. Businesses can create personalized content at an unprecedented rate, with deeper insight into their target customers than ever before. If harnessed correctly, generative AI promises to be incredibly valuable for businesses searching for growth in the long term.

The trend is growing fast, and more companies worldwide are beginning to adopt it each day. To stay on top of this trend and ensure that generative AI works for you strategically, let InspiringApps help manage your software development process by viewing our development work today—because the future starts now!

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Building an Inspiring Business Using AI & Automation

CEO Brad Weber of InspiringApps joined Adam Torres on the Mission Matters Podcast to announce his new book and dive into InspiringApps’ latest insights on the business applications of artificial intelligence. The discussion explores challenges and lessons learned in growing a company, emphasizing the significance of a strong team and strategic decision-making, and predicting the future of AI from revolution to best practice. Watch the Podcast Key Takeaways AI & Automation AI is transforming how we create solutions. Artificial intelligence (AI) has become a significant force in our lives, particularly through our mobile devices. AI can predict our routes and provide traffic information, making it a useful tool for automation and more. Representing one specific type of AI, ChatGPT has gained popularity because of its ability to generate content. However, there has been a backlash due to concerns about copyright infringement. Despite this, companies like InspiringApps are finding ways to integrate generative AI capabilities into products, creating more targeted solutions for consumers. We need to approach AI implementation thoughtfully. Overall, AI presents both opportunities and challenges for businesses, and it’s crucial to approach its implementation thoughtfully. While some see potential benefits, others worry about job security. For example, starting out as a copywriter in this space may be challenging, as entry-level positions could be affected. Large companies initially reacted with fear to ChatGPT, but now they are seeking guidance to understand the technology better and implement best practices within their organizations. Building an Inspiring Business Complex business challenges are no match for inspirational leadership. In his chapter of the new book, Brad discusses the challenges and importance of growing a successful company and cultivating a winning culture. He emphasizes the need for a strong team and a solid organizational structure. The concept of “team” is crucial to Brad. He has found that having a cohesive leadership team and solid continuity across all roles in the organization is essential. InspiringApps invests in meeting its team’s needs and involving everyone in decision-making, making it a great place to work and keeping turnover low. Brad also addresses the idea of creating cool stuff for clients versus building a real business. He shares a personal story about being “slapped with a backhanded compliment.” In this experience, Brad came to realize the need for long-term sustainability and formalizing roles for success. InspiringApps is as nimble as a startup but as mature as an enterprise when it comes to app development capabilities. As the company continues to grow, the team recognizes the importance of understanding its strengths and bringing value to clients, whether they are startups or large enterprises. Entrepreneurship & App Development “Despite having many business degrees, I’ve made many business mistakes.” BRAD WEBER, CEO | INSPIRINGAPPS, BOULDER CO Brad shares his experiences and mistakes, hoping that others can learn from them. He believes that learning from both “triumphs and goofs” is valuable. Growing a company is fraught with risk. Cultivating a winning culture requires an employee-based team. A flat org structure will only take you so far. Create cool stuff for clients or build a real business. To get the full story on topics like these, buy the book on Amazon today!

1 year ago

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