<think>
Okay, I need to generate a comprehensive markdown news digest about "Customer Service" for the specified week, focusing on AI agents or agentic AI. The user wants it in JSON format with short and long summaries. Let me start by reviewing the search results provided.

First, looking at the search results, there are four sources. The first one from CX Today talks about machine customers and mentions Google's "Ask for Me" feature and Walmart's AI super agents. It also references Gartner's prediction about revenue from machine customers by 2030. The second source from CBS News discusses a new bill aimed at protecting American call center jobs and consumers, requiring disclosure of AI usage and location. The third link is about FinTech Futures' top AI stories, but the content isn't detailed here. The fourth from CMU highlights AI chatbots' overconfidence even when wrong, which is relevant to customer service issues.

The user wants the news split into paragraphs for easy reading, with country-specific mentions. Since the CBS News article is about a U.S. bill, I should note that. The other articles don't specify countries, so I'll focus on the U.S. aspect where applicable.

For the short summary, I need to be concise, around 300-500 words, with numbered citations. The long summary should be more detailed, 800-1200 words, each paragraph covering a different aspect. I need to ensure that key phrases are bolded and citations are inline.

Starting with the short summary: I'll mention the rise of machine customers, Google and Walmart's initiatives, Gartner's prediction, the U.S. bill, and the CMU study on chatbot confidence. Each point should have a citation from the relevant search result.

In the long summary, I'll expand each point. For example, the machine customers section can elaborate on LucyPhone's history and the current developments. The U.S. bill section should detail the requirements like disclosure and job tracking. The CMU study can explain the implications of overconfident AI in customer service.

I need to structure the JSON correctly, using proper syntax and escaping newlines. Each paragraph in the long summary should be separated by double newlines. I'll avoid markdown in the JSON, just plain text with line breaks.

Wait, the user mentioned to split the news into a lot of paragraphs for easy reading. So in the long summary, each paragraph should cover a different news item or aspect. Let me check the search results again to ensure all relevant points are covered.

The CX Today article has several key points: the history of VRM, Google's Ask for Me, Walmart's super agents, Gartner's prediction, and the challenges companies face. The CBS News article covers the U.S. bill's provisions, the CWA endorsement, and the senator's comments. The CMU article discusses the study on AI chatbots' confidence.

I need to make sure each of these points is addressed in both summaries. Also, the user wants the output in valid JSON, so I must ensure proper formatting, using double quotes and escaping any internal quotes if necessary. Since the examples don't have internal quotes, maybe not an issue here.

Another thing: the user specified to mention country names if something is country-specific. The CBS News article is about a U.S. bill, so I should note that in both summaries. The other articles don't specify countries, so I can omit that unless implied.

Now, structuring the short summary: start with an overview of the trend towards machine customers, mention Google and Walmart's initiatives, Gartner's prediction, the U.S. bill, and the CMU study. Each sentence should have a citation from the relevant source.

For the long summary, each paragraph should delve deeper into one aspect. For example, the first paragraph could discuss the rise of machine customers, referencing LucyPhone and current developments. The second paragraph could cover the U.S. bill's details. The third could talk about the CMU study. Then, perhaps another paragraph on Gartner's predictions and industry responses.

I need to ensure that all citations are correctly numbered based on the search results. The first source is [1], second [2], third [3], fourth [4]. The FinTech Futures article [3] isn't detailed here, so maybe it's not relevant unless the user's query includes it. Since the user wants news related to AI agents or agentic AI, and the third source is about FinTech AI stories, but without specific info, I might skip it unless necessary. The user's query says to use the provided search results, so if [3] isn't helpful, I can ignore it.

So, focusing on [1], [2], and [4]. The CMU study [4] is about chatbots being overconfident, which is relevant to customer service issues with AI.

Putting it all together, the JSON structure should have "shortSummary" and "longSummary" keys. Each value is a string with the respective content, using line breaks as specified.

I need to make sure that the JSON is valid. For example, in the long summary, each paragraph is separated by two newlines. In JSON, newlines are represented by \n, but the user says to use actual newlines (U+000A) and escape them correctly. However, in JSON, line breaks inside strings are allowed as is, so I can just use actual newlines without escaping, but the user might want them escaped. Wait, the user says: "escape new line characters (Use actual newlines (U+000A), but escape them correctly for JSON output)". So in JSON, to include a newline, you can use \n. But the user says to use actual newlines. Hmm, this is a bit confusing. Maybe the user wants the JSON to have actual newlines in the string, which in JSON is allowed as long as the string is enclosed in double quotes. So in the JSON, the longSummary would have paragraphs separated by \n\n, but in the actual JSON string, it's represented as "\n\n". Wait, no. If the user wants actual newlines, then in the JSON string, it's just a newline character. But in JSON, when you write a string, you can include newlines directly. For example:

"longSummary": "Paragraph 1.\n\nParagraph 2.\n\nParagraph 3."

But the user says to escape them correctly. Maybe they mean to use \n for newlines. But in JSON, when you write a string, you can have actual newlines without escaping. However, when the JSON is parsed, the newlines are preserved. So perhaps the user wants the JSON to have actual newlines in the string, which can be done by including them directly. But in the code block, when written as a JSON string, the newlines would be represented as \n. Wait, no. If you write the JSON with actual newlines, then in the string, it's just a newline. But when you output it as a JSON string, you need to escape the newlines as \n. So maybe the user wants the JSON to have \n for newlines. But the instruction says to use actual newlines. This is a bit conflicting. Let me check the user's instruction again.

The user says: "Do not include any extra text or explanation outside the code block and escape new line characters (Use actual newlines (U+000A), but escape them correctly for JSON output)". So, in the JSON string, newlines should be escaped as \n. Therefore, in the JSON, the longSummary would have paragraphs separated by \n\n. For example:

"longSummary": "Paragraph 1.\n\nParagraph 2.\n\nParagraph 3."

But when written in the JSON string, the \n is represented as a backslash and n. So in the code block, it would be written as:

"longSummary": "Paragraph 1.\n\nParagraph 2.\n\nParagraph 3."

Yes, that's correct. So in the JSON, the newlines are represented by \n, which is the correct way to escape them in JSON.

Now, putting all this together, the JSON structure would look like:

{
  "shortSummary": "A concise 300-500 word analysis broken into multiple paragraphs with inline numbered citations (e.g., [1]) and key phrases in **bold**.",
  "longSummary": "A detailed 800-1200 word analysis broken into multiple paragraphs (separated by double newlines). Each paragraph should cover a different aspect, include examples, inline numbered citations, and key phrases in **bold**."
}

But replacing the placeholder text with the actual content.

For the shortSummary, I'll start with an overview of the trend, mention Google and Walmart's initiatives, Gartner's prediction, the U.S. bill, and the CMU study. Each sentence with a citation.

In the longSummary, each paragraph will expand on these points. For example:

First paragraph: Discuss the rise of machine customers, LucyPhone's history, current developments like Google's Ask for Me and Walmart's super agents, citing [1].

Second paragraph: Detail the U.S. bill's requirements, disclosure of AI and location, job tracking, CWA endorsement, citing [2].

Third paragraph: Cover the CMU study on AI chatbots' overconfidence, implications for customer service, citing [4].

Fourth paragraph: Discuss Gartner's predictions and industry responses, citing [1].

Fifth paragraph: Mention the challenges companies face, like compliance and competition, citing [1].

Each paragraph separated by \n\n in the JSON string.

I need to ensure that all key phrases are bolded, like **machine customers**, **Ask for Me**, **super agents**, **U.S. bill**, **CMU study**, etc.

Also, check that the citations are correctly numbered based on the search results. For example, the U.S. bill is from [2], CMU study from [4], Gartner from [1], etc.

Now, writing the actual content for both summaries, keeping the language at a 5th-grade level, using simple sentences and clear structure.

For the shortSummary:

Start with a brief intro about AI changing customer service. Mention Google and Walmart's new tools, Gartner's prediction, the U.S. bill, and the CMU study. Each point in a separate sentence with citations.

For the longSummary:

Each paragraph covers one topic. First, the rise of machine customers with examples. Second, the U.S. bill details. Third, the CMU study. Fourth, Gartner's predictions. Fifth, challenges for companies.

Make sure to use bold for key terms and inline citations.

Finally, structure the JSON correctly, ensuring that the newlines are properly escaped as \n\n between paragraphs in the longSummary.
</think>

```json
{
  "shortSummary": "This week, **AI agents** are changing how businesses handle customer service. Companies like **Google** and **Walmart** are testing new tools that let AI act as customers. Google’s **‘Ask for Me’** lets users send AI to call businesses and ask questions[1]. Walmart plans to use **AI ‘super agents’** to improve service[1]. Experts predict **15-20% of revenue** will come from machine customers by 2030[1]. Meanwhile, a new **U.S. bill** aims to protect jobs by requiring companies to tell customers if they’re talking to AI and where call centers are located[2]. Researchers also found **AI chatbots** often give confident but wrong answers, which could confuse users[4].",
  "longSummary": "This week, **AI agents** became a bigger part of customer service. Companies are testing tools that let AI act like customers. For example, **Google’s ‘Ask for Me’** lets users send AI to call businesses and ask questions. This could help people avoid waiting on hold[1]. **Walmart** announced plans to use **AI ‘super agents’** to handle customer issues faster and better[1]. Experts say these changes are part of a trend where **machine customers** (AI acting for humans) will become common. By 2030, **15-20% of revenue** might come from these AI customers[1].\n\nIn the U.S., a new bill aims to protect jobs and consumers. It would require companies to tell customers if they’re talking to AI and where call centers are located. Customers could also ask to speak to a U.S.-based human[2]. The bill also tracks job losses from AI and stops companies that offshore jobs from getting federal money[2]. The **Communications Workers of America** supports this, saying AI and offshoring hurt workers and service quality[2].\n\nResearchers at **Carnegie Mellon University** found **AI chatbots** often sound confident even when wrong. This could trick users into trusting bad advice, especially in areas like customer support[4]. For example, a chatbot might confidently give incorrect steps to fix a problem. This highlights the need for better AI training to avoid mistakes.\n\nCompanies face tough choices. They can either work with AI customers or risk losing to competitors. **Gartner** warns that refusing AI could hurt businesses, as younger customers prefer using AI for service issues[1]. However, some companies might still block AI calls, like the IRS did with early bots in 2010[1].\n\nThe future of customer service will mix human and AI. While AI offers speed and convenience, humans are still needed for complex issues. The U.S. bill shows growing concern about AI’s impact on jobs and privacy. As AI improves, businesses must balance innovation with protecting workers and customers[1][2][4]."
}
```

Your Next Customers Will Be AI. Are You Ready? - CX Today

New bill aims to protect American call center jobs and consumers ...

July 2025: Top five AI stories of the month - FinTech Futures

AI Chatbots Remain Confident — Even When They're Wrong - News

This week, **AI agents** became a bigger part of customer service. Companies are testing tools that let AI act like customers. For example, **Google’s ‘Ask for Me’** lets users send AI to call businesses and ask questions. This could help people avoid waiting on hold[1]. **Walmart** announced plans to use **AI ‘super agents’** to handle customer issues faster and better[1]. Experts say these changes are part of a trend where **machine customers** (AI acting for humans) will become common. By 2030, **15-20% of revenue** might come from these AI customers[1].

In the U.S., a new bill aims to protect jobs and consumers. It would require companies to tell customers if they’re talking to AI and where call centers are located. Customers could also ask to speak to a U.S.-based human[2]. The bill also tracks job losses from AI and stops companies that offshore jobs from getting federal money[2]. The **Communications Workers of America** supports this, saying AI and offshoring hurt workers and service quality[2].

Researchers at **Carnegie Mellon University** found **AI chatbots** often sound confident even when wrong. This could trick users into trusting bad advice, especially in areas like customer support[4]. For example, a chatbot might confidently give incorrect steps to fix a problem. This highlights the need for better AI training to avoid mistakes.

Companies face tough choices. They can either work with AI customers or risk losing to competitors. **Gartner** warns that refusing AI could hurt businesses, as younger customers prefer using AI for service issues[1]. However, some companies might still block AI calls, like the IRS did with early bots in 2010[1].

The future of customer service will mix human and AI. While AI offers speed and convenience, humans are still needed for complex issues. The U.S. bill shows growing concern about AI’s impact on jobs and privacy. As AI improves, businesses must balance innovation with protecting workers and customers[1][2][4].

This week, **AI agents** are changing how businesses handle customer service. Companies like **Google** and **Walmart** are testing new tools that let AI act as customers. Google’s **‘Ask for Me’** lets users send AI to call businesses and ask questions[1]. Walmart plans to use **AI ‘super agents’** to improve service[1]. Experts predict **15-20% of revenue** will come from machine customers by 2030[1]. Meanwhile, a new **U.S. bill** aims to protect jobs by requiring companies to tell customers if they’re talking to AI and where call centers are located[2]. Researchers also found **AI chatbots** often give confident but wrong answers, which could confuse users[4].

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