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Coming for Your Job or Improving Your Performance?

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Epic’s Electronic Medical Record and Ancillary Systems Release AI Upgrades

Epic Systems announced a host of artificial intelligence (AI) tools last month at its annual conference. With its more than 300 million patient records (in a country with <400 million people) and more than 3500 different hospital customers, Epic has either released or is currently working on more than 200 different AI tools.1

Their vast data stores are being used to create predictive models and train their own AI tools. The scale of Epic and AI and what it can be used for is both exciting and frightening.

Optimizing Tools to Reduce the Burden of Health Care Administration

Typically, Epic Systems and other technology solution providers’ first entry into AI implementation comes in the form of reducing menial tasks and attempting to automate patient-customer interactions. In my discussions with health care administrators, it is not uncommon for them to attribute 40% to 60% of the cost of health care to administrative tasks or supports. For every physician, there are generally at least 3 full-time equivalencies (workforce members) needed to support that physician’s work, from scheduling to rooming patients to billing and a host of other support efforts.

About the Author

Troy Trygstad, PharmD, PhD, MBA, is the executive director of CPESN USA, a clinically integrated network of more than 3500 participating pharmacies. He received his PharmD and MBA degrees from Drake University and a PhD in pharmaceutical outcomes and policy from the University of North Carolina. He has recently served on the board of directors for the Pharmacy Quality Alliance and the American Pharmacists Association Foundation. He also proudly practiced in community pharmacies across the state of North Carolina for 17 years.

Reducing Cost and Improving Patient-Customer Experience

Reducing administration should reduce costs. Early-entry AI tools are generally aimed at reducing administrative cost, while simultaneously improving the patient experience extramural to the care delivery process (the bump in customer experience is the side benefit, not the motivation). In fact, all of us are more likely to be assigned an AI assistant as a customer than to use one as a health care provider at this juncture. AI is currently deployed over multiple sectors and customer service scenarios, interacting with us indirectly in recent years and now more directly as time passes. Remember that Siri and Alexa continue to grow just like humans, and now there are thousands and thousands of these AI bots. There is a strong possibility that if you answer a spam phone call, the “person” on the other end of the line is an AI tool (being?) and not a human.

Will AI Be an Antidote to Health Care Professional Burnout?

Charting is a drag. Ask any medical provider and one of their least favorite tasks is writing patient encounters for documentation’s sake rather than for the sake of patient care. I’ve personally known hundreds of physicians over my 2 decades of collaborating with them and the majority do most of their charting during off hours (thanks to technology), eating into their work-life balance and wellbeing. A recent study of providers using AI tools for charting found a 40% reduction in documentation burden and better and more complete charting.2 Could AI reduce the burden of menial pharmacy tasks that take away from patient care as well? Very likely yes.

But what if the business model doesn’t change? The biggest lie ever told in pharmacy was that technology was going to free pharmacists to provide patient care without a subsequent workflow and economic model to support it. Therefore, our profession went from filling 150 prescriptions a day to 300 a day to, in some cases, up to 500 per day per pharmacist. The only thing the technology did was increase the throughput of the existing business model. It didn’t support a new model at all.

That is the concern of many physicians as well. Will AI merely increase the number of encounters expected of them or will it actually improve their care delivery and practice satisfaction? That’s a question explored in a recent Harvard Business School article that points to upcoding bias (documentation of higher levels of care to bill more revenue), reduction in administrative cost, and reduced clerical full-time equivalents as the seeming “wins” for health systems administrators thus far, rather than better and more cost-efficient care delivery overall.3 Unsurprisingly to pharmacists, the business model is driving AI use, not the desired practice model.

AI as the New “Peripheral Brain” and Decision Support System

Those of us of a certain age remember a time in pharmacy school when we first entered the practice world under the supervision of a preceptor. At that time, the “peripheral brain” was a notebook that contained the latest prescribing guidelines, infectious disease–drug matches, and other clinical information. Then along came a handheld electronic version of it. Then came Google. Then the implementation of cloud computing. And now AI.

AI is already in place for many physicians and other health care providers, and I fear pharmacy may actually be late to the game in an arms race to make the drug assessment–prescribing–filling process even more efficient. But efficient at what? Administrative tasks? Order entry? Prior authorization documentation?

What About the Effects on Health System and Community Pharmacy Practice?

What if the rest of the world views the practice of pharmacy as consisting entirely of administrative tasks and not assessment and care delivery? If the AI tool is the physician’s peripheral brain, why is there a need for the pharmacist to make recommendations or find drug therapy problems? If the AI tool is instructing the care manager on which medications the care team needs to gather information about and report back to the peripheral brain, why have a pharmacist on the team? There will be many who say, “Oh, AI will absolutely replace the need for pharmacists because they don’t (actually) deliver care. They are a means of medication distribution and a great source of knowledge of medications, but AI will be better at that.”

Too Little Discussion and Planning Not Underway in Pharmacy Circles

The AI takeover is not some distant future reality. The reality is weeks and months away, not years and decades. Nvidia (the chipmaker essential for AI processing) has seen its stock price rise more than 900% in the past 3 years as investors awaken to the speed with which AI is moving. AI is already starting to move from helper to replacement for many jobs and we could see AI agents doing research autonomously within 6 to 18 months and becoming the experts in every field of study known to humans by 2030 (or sooner).

What are we doing in the pharmacy world to prepare, take advantage of, and plant our flag as the medication optimization experts that utilize AI better than anyone else? As far as I can tell at this juncture, we’ve given AI a passing glance and are waiting for AI to come to us, rather than aligning and integrating with AI at the outset.

AI Could Be the Best and Worst Thing for Pharmacy. We Must Learn Lessons From the Past.

There is so much work to do, from regulatory discussions with our state boards of pharmacy to scoping the future of practice alongside technology solution providers to teaching the next generation of pharmacists as well as those already in practice about how to use AI to deliver safer, more effective, and more innovative care.

And above all, practice follows the business model. If provider status was important pre-AI, it has become critical post AI. If we are a profession of clerical work, we will be replaced. If we are a profession of providers, we will harness the immense capabilities of our future AI assistants. No more “This will save you time so you can care for patients” baloney, when there is no economic support model for care delivery sizable enough to employ a quarter of a million pharmacists. We should all be demanding to see evidence of the billable time from our employers, policy makers, and regulators. That is the only sustainable path when the peripheral brain is in the cloud and is the known universe’s best version of it.

REFERENCES
1. What health care provisions of the One Big Beautiful Bill Act mean for states. National Academy for State Health Policy. July 8, 2025. Accessed July 21, 2025. https://nashp.org/what-health-care-provisions-of-the-one-big-beautiful-bill-act-mean-for-states/
2. Graham J. The big, beautiful health care squeeze is here: what that means for your coverage. Investor’s Business Daily. July 18, 2025. Accessed July 21, 2025. https://www.investors.com/news/big-beautiful-bill-trump-budget-health-care-coverage/
3. Constantino AK. Bristol Myers Squibb, Pfizer to sell blockbuster blood thinner Eliquis at 40% discount. CNBC. July 17, 2025. Accessed July 21, 2025. https://www.cnbc.com/2025/07/17/bristol-myers-squibb-pfizer-to-sell-eliquis-at-40percent-discount.html



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Which countries are producing more AI Researchers? Where does India stand? – WION

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Which countries are producing more AI Researchers? Where does India stand?  WION



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3 Artificial Intelligence ETFs to Buy With $100 and Hold Forever

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If you want exposure to the AI boom without the hassle of picking individual stocks, these three AI-focused ETFs offer diversified, long-term opportunities.

Artificial intelligence (AI) has been a huge catalyst for the portfolios of many investors over the past several years. Large tech companies are spending hundreds of billions of dollars to build out their AI hardware infrastructure, creating massive winners like semiconductor designer Nvidia.

But not everyone wants to go hunting for the next big AI winner, nor is it easy to know which company will stay in the lead even if you do your own research and find a great artificial intelligence stock to buy. That’s where exchange-traded funds (ETFs) can help.

If you’re afraid of missing out on the AI boom, and have around $100 to invest right now, here are three great AI exchange-traded funds that will allow you to track some of the biggest names in artificial intelligence, no matter who’s leading the pack.

Image source: Getty Images.

1. Global X Artificial Intelligence and Technology ETF

The Global X Artificial Intelligence and Technology ETF (AIQ 0.87%) is one of the top AI ETF options for investors because it holds a diverse group of around 90 stocks, spanning semiconductors, data infrastructure, and software. Its portfolio includes household names like Nvidia, Microsoft, and Alphabet, alongside lesser-known players that give investors exposure to AI companies they might not otherwise consider.

Another strength of AIQ is its global reach: the fund invests in both U.S. and international companies, providing broader diversification across the AI landscape. Of course, this targeted approach comes at a cost. AIQ’s expense ratio of 0.68% is slightly higher than the average ETF (around 0.56%), but it’s in line with other AI-focused funds.

Performance-wise, the Global X Artificial Intelligence and Technology ETF has rewarded investors. Over the past three years, it gained 117%, trouncing the S&P 500‘s 63% return over the same period. While past performance doesn’t guarantee future results, this track record shows how powerful exposure to AI-focused companies can be.

2. Global X Robotics and Artificial Intelligence ETF

As its name suggests, the Global X Robotics and Artificial Intelligence ETF (BOTZ -0.21%) focuses on both robotics and artificial intelligence companies, as well as automation investments. Two key holdings in the fund are Pegasystems, which is an automation software company, as well as Intuitive Surgical, which creates robotic-assisted surgical systems. And yes, you’ll still have exposure to top AI stocks, including Nvidia as well.

Having some exposure to robotics and automation could be a wise long-term investment strategy. For example, UBS estimates that there will be 2 million humanoid robots in the workforce within the next decade and could reach 300 million by 2050 — reaching an estimated market size of $1.7 trillion.

If you’re inclined to believe that robotics is the future, the Global X Robotics and Artificial Intelligence ETF is a good way to spread out your investments across 49 individual companies that are betting on this future. You’ll pay an annual expense ratio of 0.68% for the fund, which is comparable to the Global X Artificial Intelligence and Technology ETF’s fees.

The fund has performed slightly better than the broader market over the past three years — gaining about 68%. Still, as robotics grows in the coming years, this ETF could be a good place to have some money invested.

3. iShares Future AI and Tech ETF

And finally, the iShares Future AI and Tech ETF (ARTY 1.72%) offers investors exposure to 48 global companies betting on AI infrastructure, cloud computing, and machine learning.

Some of the fund’s key holdings include the semiconductor company Advanced Micro Devices, Arista Networks, and the AI chip leader Broadcom, which just inked a $10 billion semiconductor deal with a large new client (widely believed to be OpenAI). In addition to its diversification across AI and tech companies, the iShares Future AI and Tech ETF also has a lower expense ratio than some of its peers, charging just 0.47% annually.

The fund has slightly underperformed the S&P 500 lately, gaining about 61% compared to the broader market’s 63% gains over the past three years. But with its strong diversification among tech and AI leaders, as well as its lower expense ratio, investors looking for a solid play on the future of artificial intelligence will find what they’re looking for in this ETF.

Chris Neiger has no position in any of the stocks mentioned. The Motley Fool has positions in and recommends Advanced Micro Devices, Alphabet, Arista Networks, Intuitive Surgical, Microsoft, and Nvidia. The Motley Fool recommends Broadcom and recommends the following options: long January 2026 $395 calls on Microsoft and short January 2026 $405 calls on Microsoft. The Motley Fool has a disclosure policy.



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Companies Bet Customer Service AI Pays

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Klarna’s $15 billion IPO was more than a financial milestone. It spotlighted how the Swedish buy-now-pay-later (BNPL) firm is grappling with artificial intelligence (AI) at the heart of its operations.

Back in 2023, Chief Executive Sebastian Siemiatkowski suggested AI could replace large parts of the company’s customer-service workforce. The remarks sparked pushback from employees and skepticism from customers, many of whom doubted whether the technology was advanced enough to provide empathy and reliability at scale.

Pivoting and Learning

Klarna’s first wave of AI adoption proved too rigid, with customers finding the experience inconsistent. The company now pivoted toward a blended approach: AI for speed and scale, humans for empathy and trust. That adjustment echoes a lesson resonating across industries. AI works best when it augments, rather than replaces, human agents.

The company’s focus on human-powered customer support shows how the firm is hiring again to ensure customers always have the option of speaking to a person. “From a brand perspective, a company perspective, I just think it’s so critical that you are clear to your customer that there will be always a human if you want,” Siemiatkowski told Bloomberg News, as reported by PYMNTS.

As Vinod Muthukrishnan, vice president and chief operating officer of Webex Customer Experience Solutions at Cisco, explained, many financial institutions are moving past pilots and into deployment.

“These firms are increasingly leveraging their AI focus on hyper-personalized CX [customer experience] such as personal financial advice or dynamic credit limit adjustments and offers, all enabled via real-time analytics,” he told PYMNTS. Retailers and service providers face similar opportunities, provided they align strategy with measurable ROI.

Five Areas for AI, Customer Care

1. Proactive Issue Resolution

AI can anticipate problems before customers complain. Declined payments, unexpected fees or delivery delays can be flagged and addressed in real time, turning frustration into loyalty. Most firms still operate reactively, in part because data remains siloed across payments, logistics and support and closing these gaps could sharply reduce call volumes.

2. Hyper-Personalized Support

Consumers now expect service that reflects their history and preferences. AI can tailor repayment options, loyalty incentives, or offers based on real-time data. Walmart, for example, has deployed AI-powered personalization tools to refine its app and eCommerce experience. Predictive analytics can also flag anomalies that suggest fraud or disputes, thereby reducing chargebacks. Yet many retailers still rely on generic scripts.

3. Multilingual, 24/7 Coverage

Global commerce does not keep office hours. AI chatbots and voice systems provide round-the-clock, multilingual support. New multimodal systems can handle voice, text, and even images, creating richer customer interactions. PYMNTS has reported that customers value this always-on flexibility, but many firms still lean on nine-to-five call centers or outsourced night shifts.

4. Sentiment Detection and Emotional Intelligence

Speed matters, but empathy builds loyalty. AI can read tone and phrasing in real time, alerting human agents when a customer is upset. This hybrid model ensures efficiency without sacrificing trust. Rezolve’s Brain Suite applies empathy-driven AI to reduce cart abandonment, which accounts for nearly 70% of lost online sales. Yet sentiment detection remains rare in many call centers.

5. Insights Beyond the Call Center

Complaints can expose flaws in checkout flows, packaging or design. AI can analyze these patterns, turning customer service into a source of business intelligence. Google’s Vision Match tools, for example, feed insights from shopping behavior back into product strategy. Few enterprises close this loop.

ROI as the Deciding Factor

For executives, ROI is the real test. Projects that fail to deliver lower handle times, better satisfaction scores, or reduced churn rarely scale. “AI as with any new technology risks adoption and integration without a clear strategic alignment,” Muthukrishnan warned. “Too many pilots or implementations can lead to a fragmented focus.”

 “We’re already in market with our AI agent for autonomous and scripted self-service,” Todd Fisher, CEO and co-founder of CallTrackingMetrics, told PYMNTS.  

In a recent survey, 72% of respondents rated Webex AI Agent as equal, if not better, than a human agent. And our customers have reported an 85% reduction in agent call escalations, a 22% reduction in average handle time, and a 39% increase in CSAT [customer satisfaction] scores.” 



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