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For AI success, turn change resistance into change resilience :: WRAL.com

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Executives worldwide are asking the same question: If artificial
intelligence (AI) is such a transformational force, why isn’t my company seeing
bigger results?

Despite the relentless hype, most organizations are still
struggling to turn AI investments into measurable business outcomes. Only 26%
of companies report tangible bottom-line benefits from AI, according to a Boston
Consulting Group survey
of 1,000 global executives. Some leaders are
getting it right — 45% of these early adopters have seen lower costs, and 60%
report higher revenue growth than their peers. But for many more, the ROI is
still elusive.

The biggest obstacle isn’t technology. It’s people.

In the 2025
AI & Data Leadership Executive Benchmark Survey
, 92% of respondents
said cultural resistance and change management challenges are slowing AI
adoption. Or, as Michael Wade and his co-authors write in MIT
Sloan Management Review
, “It is the human side of the equation that
determines whether Gen[erative] AI initiatives truly succeed. … Success hinges
not just on infrastructure but on how people think, adapt, and collaborate with
AI.”

The takeaway is clear: AI success isn’t about having the
right tools. It’s about turning change resistance into change resilience.

Identify the roots of resistance

In sales, the key to success is understanding the needs of
your client and framing your product as a solution to those pain points.
Selling your workforce on the advantages of AI is no different. To drive
meaningful change, leaders must first understand why employees are hesitating.

Workers might feel skeptical about the technology, especially
if they aren’t sure how it will personally help them.  And, if previous technological breakthroughs
have resulted in layoffs and restructuring, employees might feel greater
pressure to perform or be afraid of losing their jobs.

The only way to calm fear and uncertainty is with empathy
and communication. As renowned negotiator Chris Voss, co-author of “Never Split
the Difference,” explains in The New York Times, “When someone feels
thoroughly understood, you release potent forces for change within them.”

As I’ve written before, consistent
communication
demonstrates that you care about employees, their challenges
and their well-being. This is the key to authentic empathy. When implementing a
change as monumental as AI integration, check in often with your team. Approach
these conversations with psychological safety in mind, so employees will be
more likely to come to you with their concerns. Ask them how they are feeling,
what they need and what their challenges are.

Leaders who listen with empathy and understanding can shift
the narrative from AI as a threat to AI as an opportunity.

Quality, not just quantity

CEOs and other senior executives are rightly excited about
the promise of AI to save time and increase productivity. Here’s the problem:
If you lead with that argument, your employees aren’t going to hear
“efficiency,” they’re going to hear “redundancy.”

If AI is framed only as a cost-saving measure, your adoption
strategy will suffer. Instead, focus on how AI enhances quality. Explain how it
frees people from mundane or repetitive tasks, so they can spend more time on deeper
thinking and creative problem-solving. Show how it creates capacity for
higher-value work and more meaningful human interaction.

That shift in framing is critical. Efficiency is a company
benefit. Quality is an individual benefit. And unless employees see personal
value, they won’t embrace the tools.

How you talk about AI in everyday conversations matters as
well. People want their contributions to matter, and if leaders describe
AI-created outputs as “better” or preferable to those created by a human, employees
may feel that their work isn’t valued or appreciated.

Your message should be consistent: AI is an assistant and thought
partner that amplifies human skills. It’s not
here to replace human expertise. It’s here to multiply it.

People-first strategies for AI integration

To succeed, AI adoption must be approached as a people
strategy as well as a business transformation. Leaders can reduce resistance
and accelerate resilience with the following practices:

1.      
Build trust with transparency.
Change is unsettling, so leaders should be clear about why AI is being implemented,
how it will affect employees, and what steps will be taken to support them
through the transition. Communicate clearly about ethical safeguards, training
opportunities and job impacts. 

2.      
Cultivate a growth
mindset.
Encourage employees to ask questions, experiment with
various AI tools, and contribute new ideas. Provide opportunities for feedback
and peer support. When people are involved in the process, they are less likely
to see AI as a threat.

3.      
Create a meaningful message. Instead of
framing AI as a cost-saving tool, explain how the technology can be used to
eliminate mundane tasks. Emphasize how AI can help employees be more creative
or produce higher-quality work. Consistently describe AI as an assistant, not a
replacement, for skilled team members.

4.      
Invest in training and upskilling. Ensure
employees feel equipped to use AI in their day-to-day work. Include training
with other professional development opportunities, promoting it as adding
lasting career skills. Encourage peer-to-peer learning to build
confidence.

Empathy inspires resilient cultures

AI is already reshaping the future of work, and organizations
will have to adapt. The companies that will thrive in this new environment will
be led by empathetic leaders who cultivate resilient cultures. Employees will
see AI as a partner in their success, not a threat to their survival.

To realize the tangible benefits of AI, leaders must go
beyond implementation to inspiration. It’s not enough to install new systems;
you must build trust, communicate with clarity, and empower your people to grow
with the technology.

The bottom line? Resistance is natural. Resilience is
intentional. If you want your workforce to embrace AI, start by treating
adoption as a human challenge — not just a technical one. The organizations that
get this right will unlock not just productivity, but the creativity, loyalty and discretionary effort that only people can deliver.

About the Author     

Donald Thompson,
EY Entrepreneur Of The Year® 2023 SE Award-winner, founded The
Diversity Movement, a Workplace Options Company, to fundamentally transform the
modern workplace through diversity-led culture change. Recognized by Inc.,
Fast Company and Forbes, Thompson is author of Underestimated:
A CEO’s Unlikely Path to Success
,
hosts the podcast “High Octane Leadership in an
Empathetic World
” and has published widely on leadership and
the executive mindset. His latest book is The
Inclusive Leadership Handbook
: Balancing People and Performance for
Sustainable Growth
, co-authored with Kurt Merriweather, Vice
President of Global Marketing at Workplace Options. Follow Thompson on LinkedIn
for updates on news, events and his podcast, or contact him at info@donaldthompson.com
for executive coaching and speaking engagements.  

 



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Lomas: Artificial Intelligence in mining – An illusion or a revolution? – Elko Daily Free Press

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Lomas: Artificial Intelligence in mining – An illusion or a revolution?  Elko Daily Free Press



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FDA plans advisory committee meeting on AI mental health devices

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Mario Aguilar covers technology in health care, including artificial intelligence, virtual reality, wearable devices, telehealth, and digital therapeutics. His stories explore how tech is changing the practice of health care and the business and policy challenges to realizing tech’s promise. He’s also the co-author of the free, twice weekly STAT Health Tech newsletter. You can reach Mario on Signal at mariojoze.13.

The Food and Drug Administration will convene experts to discuss challenges around regulating mental health products that use artificial intelligence, as a growing number of companies release chatbots powered by large language models whose output can be unpredictable. 

The move suggests the agency may soon tighten its focus on such tools.

The Nov. 6 meeting of the FDA’s Digital Health Advisory Committee (DHAC) will focus on “Generative Artificial Intelligence-Enabled Digital Mental Health Medical Devices,” according to a notice published Thursday in the Federal Register. The notice says newly released mental health products using AI pose “novel risks and, as mental health devices continue to evolve in complexity, regulatory approaches ideally will also evolve to accommodate these novel challenges.” 

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Inside Apple’s Artificial Intelligence Strategy

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Apple’s artificial intelligence strategy has become something of a paradox: A company famed for redefining consumer technology is now seen as trailing behind in the generative AI boom. Siri, hyped for years as a next-generation personal assistant, falls short of latecomers like Google Assistant and ChatGPT in intelligence and contextual awareness. And the recent debut of the iPhone 17 barely mentioned Apple Intelligence, its AI system that is still largely in the making. 

To this day, the lion’s share of Apple’s AI capabilities are outsourced to third-party systems — an awkward position for a company long renowned for innovation. Now, many are wondering if the world’s most valuable brand will step back for good, let leaders like Google or OpenAI take the lead, and stay squarely in its hardware roots. 

What Is Apple’s AI Strategy?

Apple’s approach to artificial intelligence appears to be slow, yet deliberate. Instead of building massive, general-purpose language models and public-facing chatbots, the company favors small acquisitions, selective partnerships and in-house developments that emphasize privacy and on-device processing.

But, despite the perception of being slow, Apple’s approach follows a familiar pattern. The company has always avoided making splashy acquisitions, instead folding in small teams and technologies strategically until it can scale in-house once the timing is right. This playbook has been repeated time after time, from Apple Maps and Music to its custom silicon chips.

So, what some see as Apple being late to the party is actually a calculated turtle-and-hare strategy playing out — or at least that’s what CEO Tim Cook says. Current partnerships with OpenAI and Anthropic keep Apple in the game while it quietly works on its own foundation models. Whether its next step involves buying, partnering or doubling down on its own research, the expectation is that Apple likely won’t stay behind forever.

Related ReadingGoogle’s Pixel 10 Pushes Smartphones Into the AI-First Era. Can Apple Catch Up?

 

Apple’s AI Strategy at a Glance

Apple’s approach to AI blends small but targeted acquisitions and carefully chosen partnerships with major players. While it hasn’t made any blockbuster moves just yet, the company seems to be quietly shaping its portfolio and shifting talent around to bring more AI development in-house.

The Acquisitions We Know About

During Apple’s third-quarter earnings call, CEO Tim Cook said the company is “very open to” mergers and acquisitions that “accelerate” its product roadmap, and “are not stuck on a certain size company, although the ones that [Apple has] acquired thus far this year are small in nature.”

Only four of these companies have been identified thus far:

  1. WhyLabs: An AI observability platform that monitors machine learning models for anomalies to ensure reliable performance. For Apple, this means more secure generative AI and optimized on-device intelligence.
  2. Common Ground: Formerly known as TrueMeeting, this AI startup focused on creating hyper-realistic digital avatars and virtual meeting experiences. Its tech is likely to fold into Apple’s Vision Pro ecosystem.
  3. RAC7: The two-person video game developer behind mobile arcade title Sneaky Sasquatch. This is Apple’s first-ever in-house studio, which will focus on creating exclusive content for Apple Arcade.
  4. Pointable AI: Three days into the year, Apple bought this AI knowledge-retrieval startup that links enterprise data feeds to large language model workflows. The platform lets Apple create reliable LLM-driven applications that can be integrated into on-device search, AI copilots and automation tools.

Internally, Apple is restructuring its ranks to prioritize AI development within the company, according to Cook.

Companies Apple Is Talking To

Apple has reportedly been exploring the purchase of Mistral AI, a French developer now valued at about $14 billion. Mistral has its own chatbot, Le Chat, which runs on its own AI models, as well as various open-source offerings, consumer apps, developer tools and a wide selection of APIs — all while sharing Apple’s hardline stance on privacy. For a while, Apple was also thinking about acquiring Perplexity, but walked away from the multi-billion-dollar deal in part due to mounting concerns over the AI search engine’s controversial web-scraping practices, which clash with Apple’s emphasis on privacy. Instead, Apple plans to become a direct competitor, beefing up its Siri product.

Meanwhile, Apple’s partnership with Anthropic has expanded significantly over the past few months. The collaboration now includes integrating Anthropic’s Claude model into Apple’s Xcode software, creating a “vibe coding” developer tool that helps write, edit and test code more efficiently. Apple is also considering Anthropic’s models in its long overdue Siri overhaul, with the new version expected to launch in early 2026. 

But it’s not the only contender. Apple confirmed to 9to5Mac that it will be integrating OpenAI’s GPT-5 model with the iOS 26’s fall launch, and has reportedly reached a formal agreement with Google to test a custom Gemini model for the virtual assistant. Internally known as “World Knowledge Answers,” this feature would let users search information from across their entire device and the web, delivering its findings in AI-generated summaries alongside any relevant text, photos, videos and points of interest in a single, digestible view. 

Together, these partnerships with Anthropic, OpenAI and Google give Apple the flexibility to test different AI systems and products and see which fits best into their existing systems, while also keeping their cards close to the chest.

How the Google Search Deal Fits In

Apple’s AI plans are also closely tied to its $20 billion-per-year search deal with Google, which makes Google’s search engine the default in Apple’s Safari browser and Siri. That contract accounts for a massive portion of Apple’s Services revenue — roughly 20 percent — giving the company the financial freedom to take a slower, more deliberate approach to AI. 

Fortunately for Apple, this deal is still allowed under Google’s recent antitrust ruling. But if regulators ever choose to limit or terminate the deal, Apple would lose a critical cash stream and be forced to build its own solution. That looming risk could force Apple’s typical cautious approach into a sprint, making partnerships, acquisitions and internal development more urgent.

Related ReadingAI-First Devices Are Coming. Could Any of Them Replace the iPhone?

 

Why Is Apple Moving Slowly on AI?

Apple’s slow pace largely stems from a push-pull standoff between two top executives at the company. Eddy Cue, the senior vice president of Services, has long championed bold acquisitions to accelerate growth, while Craig Federighi, who oversees Apple’s operating system, wants to focus on building from within. Cue’s camp believes that buying startups is the key to gaining the upper hand in AI, whereas Federighi’s side sees acquisitions as a source of complexity and cultural friction.

At this point, Apple stands in stark contrast to competitors like Google, Meta and Microsoft, which are spending billions to acquire startups and poach top AI talent with hundred-million-dollar signing bonuses and even higher compensation packages. Instead, Apple has stuck to its cautious playbook, which has probably spared it from some costly missteps over the years. But it also leaves it vulnerable. If its rivals continue to outpace it in AI investment and adoption, Apple’s reputation of being “too big to fail” may face its toughest test yet. 

 

Apple’s History of Selective  Acquisitions

Apple has made more than 100 acquisitions in its history, but almost all were small, quiet and tech-driven. Now, with $133 billion in spending money, the company has enough to make a mega AI acquisition. But, given Apple’s patterned behavior of restraint, it may choose not to — which is why the current, multi-billion-dollar speculation around the company’s next move is such a big deal.

Here is a quick look at Apple’s past money moves:

1997 — NeXT ($400 million): This was the computer company Steve Jobs founded after leaving Apple. Once acquired, it brought Jobs back to the company as well as the foundation for the operating systems used for macOS and iOS. 

2005 — FingerWorks (undisclosed amount): A startup that made gesture-recognition tech that enabled the iPhone’s multi-touch interface.

2008 – PA Semi ($278 million): Chip design firm that gave Apple the know-how to build its own silicon, leading to the A-series processors in iPhones and iPads and the M-series in Macs.

2010 – Siri ($200 million): A voice-assistant startup spun out of SRI International, Siri brought conversational AI to the iPhone and became a core iOS feature.

2012 – AuthenTec ($356 million): The fingerprint sensor company behind Touch ID.

2013 – PrimeSense (about $350 million): The 3D sensing tech that powered Face ID and AR depth cameras.

2014 – Beats Electronics ($3 billion): Apple’s largest-ever acquisition brought premium headphones, the Beats Music streaming service and key executives like Jimmy Lovine and Dr. Dre to the company, both of whom helped jumpstart Apple Music.

2018 – Shazam ($400 million): A music recognition app that was integrated into Siri and Apple Music.

2020 – Xnor.ai ($200 million): An edge AI startup that boosted Apple’s on-device, privacy-first AI by running machine learning models directly on devices, eliminating the need to send data to the cloud.

Related ReadingCan We Figure Out What Apple Is Doing With AI?

Does Apple use AI?

Yes, Apple has long incorporated artificial intelligence into its devices through features like Face ID, Siri and Apple Pay. The company’s proprietary AI system, Apple Intelligence, has been integrated across iOS, iPad OS and macOS. 

Is Apple building its own AI?

Yes, Apple is actively developing its own artificial intelligence system, called Apple Intelligence. It is also working on a massive Siri upgrade, which is slated to roll out in 2026.

What AI companies has Apple bought?

Some of the AI companies Apple has acquired over the years include:

  1. WhyLabs: An AI observability platform that monitors machine learning models for anomalies to ensure reliable performance. 
  2. Common Ground: An AI startup focused on creating hyper-realistic digital avatars and virtual meeting experiences. Its tech is likely to fold into Apple’s Vision Pro ecosystem.
  3. Pointable AI: An AI knowledge-retrieval startup that links enterprise data feeds to large language model workflows. 
  4. Siri: A voice assistant spun out of SRI International that Apple has since integrated as a core iOS feature.
  5. AuthenTec: A fingerprint sensor company that Apple used to offer Touch ID.
  6. PrimeSense: 3D sensing technology that powers Apple’s FaceID and AR depth cameras.
  7. Shazam: A music recognition app that was integrated into Siri and Apple Music.
  8. Xnor.ai: Edge AI tech used to boost Apple’s on-device, privacy-first AI by running machine learning models directly on the device, without having to send any data to the cloud.  



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