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OpenAI says ChatGPT shouldn't tell you to break up with someone

OpenAI says ChatGPT shouldn't tell you to break up with someone

Yahoo11 hours ago
OpenAI said it rolled back an earlier update of ChatGPT, which made it "too agreeable."
The company also said it has worked with health professionals to ensure ChatGPT is responding appropriately.
OpenAI said it won't measure success "by time spent or clicks."
OpenAI wants ChatGPT to help you solve life's problems — just not your relationship status.
On Monday, OpenAI announced a series of changes it's rolling out to ChatGPT to better support users during difficult times and to reflect medical expertise.
"When you ask something like 'Should I break up with my boyfriend?' ChatGPT shouldn't give you an answer," the company said in a statement about the changes. "It should help you think it through—asking questions, weighing pros and cons. New behavior for high-stakes personal decisions is rolling out soon."
Among the changes, OpenAI said it rolled back an earlier update that made ChatGPT "too agreeable." Starting on Monday, ChatGPT will also begin to prompt users with "gentle reminders" during long sessions.
"We'll keep tuning when and how they show up so they feel natural and helpful," the company said.
OpenAI said it will form an advisory group comprised of experts in mental health, youth development, and human-computer interaction. The company said it also worked with over 90 physicians across over 30 to ensure ChatGPT responds appropriately when a user shows signs of emotional distress.
OpenAI says it wants its flagship model, which the company said earlier on Monday is on track to reach 700 million weekly active users, to ensure it "genuinely" helps users rather than just holding their attention.
"Instead of measuring success by time spent or clicks, we care more about whether you leave the product having done what you came for," it said.
Read the original article on Business Insider
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Alcon Agrees to Acquire STAAR Surgical
Alcon Agrees to Acquire STAAR Surgical

Yahoo

time22 minutes ago

  • Yahoo

Alcon Agrees to Acquire STAAR Surgical

STAAR Surgical is a leader in refractive surgery using Implantable Collamer Lenses, offering solutions for moderate to high myopes Acquisition of STAAR is complementary to Alcon's laser vision correction business and is expected to be accretive in year two Alcon to purchase all outstanding shares of STAAR for $28 per share in cash, valuing STAAR at approximately $1.5 billion in equity value Ad Hoc Announcement Pursuant to Art. 53 LR GENEVA & LAKE FOREST, Calif., August 05, 2025--(BUSINESS WIRE)--Alcon (SIX/NYSE: ALC), the global leader in eye care dedicated to helping people see brilliantly, and STAAR Surgical Company (NASDAQ: STAA), the manufacturer of the Implantable Collamer® Lens (ICL), today announced the companies have entered into a definitive merger agreement through which Alcon intends to acquire STAAR. The acquisition includes the EVO family of lenses (EVO ICL™) for vision correction for patients with moderate to high myopia (nearsightedness), with or without astigmatism. Under the terms of the agreement, Alcon will purchase all outstanding shares of STAAR common stock for $28 per share in cash, which represents approximately a 59% premium to STAAR's 90-day Volume Weighted Average Price (VWAP) and a 51% premium to the closing price of STAAR common stock on August 4, 2025. The transaction represents a total equity value of approximately $1.5 billion. "With the number of high myopes rising globally, the acquisition of STAAR enhances our ability to offer a leading surgical vision correction solution for those who are not ideal candidates for other refractive surgeries such as LASIK," said David Endicott, CEO of Alcon. "This transaction will allow us to provide treatment options across the full spectrum of myopia—from contact lenses to surgical interventions—reinforcing our commitment to addressing the most significant needs in eye care." An estimated 50% of the world will be myopic by 2050 and today nearly 500 million people are considered high myopes.1 With its innovative design, the EVO family of ICLs are implantable lenses that address a wide range of vision correction needs, including myopia with and without astigmatism, through a minimally invasive procedure that is reversible. The EVO family of ICLs are implanted between the iris (the colored part of the eye) and the natural crystalline lens during a procedure that does not remove corneal tissue. "We believe the transaction with Alcon represents the best path forward and provides the greatest value for STAAR shareholders," said Stephen Farrell, CEO of STAAR. "As we've shared, fluctuating demand in China over the past two years has continued to create significant headwinds for STAAR as a standalone company. I'm proud of our team's efforts to address recent challenges, but there is more work to do. As a significantly larger company, Alcon has the capabilities and scale to accelerate EVO ICL adoption and bring our innovative technology to more surgeons and patients worldwide." Dr. Elizabeth Yeu, Chair of the STAAR Board of Directors, said, "The STAAR Board is committed to maximizing value for shareholders. We have determined that this carefully negotiated transaction is in the best interest of STAAR shareholders as it delivers immediate and certain value at a significant premium, value that exceeds what we believe could be achieved under STAAR's standalone strategy." The transaction is not subject to a financing condition. Alcon intends to finance the transaction through the issuance of short- and long-term credit facilities. The transaction is anticipated to close in approximately six to 12 months, subject to customary closing conditions, including regulatory approval and approval by STAAR's shareholders. The transaction is expected to be accretive to earnings in year two. The Boards of Directors of Alcon and STAAR have each unanimously approved the transaction. Morgan Stanley & Co. LLC is serving as financial advisor to Alcon, and Gibson, Dunn & Crutcher LLP is serving as legal advisor to Alcon. Citi is serving as the exclusive financial advisor to STAAR, and Wachtell, Lipton, Rosen & Katz is serving as legal advisor to STAAR. As previously announced, STAAR will release financial results for its second quarter that ended June 27, 2025, on Wednesday, August 6, 2025, after the market close. Given the pending acquisition by Alcon, STAAR will not host a conference call in conjunction with earnings. Forward-looking Statements This press release contains "forward-looking statements" within the meaning of the Private Securities Litigation Reform Act of 1995. All statements contained in this press release that do not relate to matters of historical fact should be considered forward-looking statements, including, without limitation, statements regarding the potential transaction between Alcon and STAAR and the expected timing, impacts and benefits thereof, Alcon's and STAAR's business strategies, performance, market adoption and estimates of market size. In some cases, you can identify forward-looking statements by terms such as "aim," "anticipate," "approach," "believe," "contemplate," "could," "estimate," "expect," "goal," "intend," "look," "may," "mission," "plan," "possible," "potential," "predict," "project," "pursue," "should," "target," "will," "would," or the negative thereof and similar words and expressions. Forward-looking statements are based on Alcon's and STAAR's management's current expectations, beliefs and assumptions and on information currently available to us. Such statements are subject to a number of known and unknown risks, uncertainties and assumptions. The following factors could cause actual results and future events to differ materially from those set forth or contemplated in the forward-looking statements: (i) the proposed merger may not be completed in a timely manner or at all, including the risk that any required regulatory approvals are not obtained, are delayed or are subject to unanticipated conditions that could adversely affect STAAR or the expected benefits of the proposed merger or that the approval of STAAR's stockholders is not obtained; (ii) the failure to realize the anticipated benefits of the proposed merger; (iii) the possibility that competing offers or acquisition proposals for STAAR will be made; (iv) risks that third parties and/or STAAR stockholders may oppose consummation of the proposed merger on the proposed terms or at all; (v) the possibility that any or all of the various conditions to the consummation of the merger may not be satisfied or waived (vi) the occurrence of any event, change or other circumstance that could give rise to the termination of the merger, including in circumstances which would require either party to pay a termination fee; (vii) the effect of the announcement or pendency of the merger on STAAR's ability to retain and hire key personnel, STAAR's ability to retain key customers, suppliers or distributors or its operating results and business generally, (viii) there may be liabilities related to the merger that are not known, probable or estimable at this time or unexpected costs, charges or expenses; (ix) the merger may result in the diversion of management's time and attention to issues relating to the merger; (x) there may be significant transaction costs in connection with the merger; (xi) legal proceedings may be instituted against STAAR following the announcement of the merger, which may have an unfavorable outcome; and (xii) STAAR's stock price may decline significantly if the merger is not consummated. In addition, a number of other important factors could cause actual future results and other future circumstances to differ materially from those expressed in any forward-looking statements, including but not limited to those important factors discussed under the heading "Risk Factors" contained in Alcon's Annual Report on Form 20-F for the fiscal year ended December 31, 2024 and in STAAR's Annual Report on Form 10-K for the fiscal year ended December 27, 2024, each as filed with the Securities and Exchange Commission ("SEC"), as such factors may be updated from time to time in such company's other filings with the SEC, accessible on the SEC's website at and the Investor Relations section of STAAR's website at and Alcon's website at All forward-looking statements are expressly qualified in their entirety by such factors. Except as required by law, neither Alcon nor STAAR undertake any obligation to publicly update or review any forward-looking statement, whether because of new information, future developments or otherwise. These forward-looking statements should not be relied upon as representing Alcon's or STAAR's views as of any date subsequent to the date of this press release. About Alcon Alcon helps people see brilliantly. As the global leader in eye care with a heritage spanning over 75 years, we offer the broadest portfolio of products to enhance sight and improve people's lives. Our Surgical and Vision Care products touch the lives of more than 260 million people in over 140 countries each year living with conditions like cataracts, glaucoma, retinal diseases and refractive errors. Our more than 25,000 associates are enhancing the quality of life through innovative products, partnerships with Eye Care Professionals and programs that advance access to quality eye care. Learn more at About STAAR Surgical STAAR Surgical (NASDAQ: STAA) is the global leader in implantable phakic intraocular lenses, a vision correction solution that reduces or eliminates the need for glasses or contact lenses. Since 1982, STAAR has been dedicated solely to ophthalmic surgery, and for 30 years, STAAR has been designing, developing, manufacturing, and marketing advanced Implantable Collamer® Lenses (ICLs), using its proprietary biocompatible Collamer material. STAAR ICL's are clinically-proven to deliver safe long-term vision correction without removing corneal tissue or the eye's natural crystalline lens. Its EVO ICL™ product line provides visual freedom through a quick, minimally invasive procedure. STAAR has sold more than 3 million ICLs in over 75 countries. Headquartered in Lake Forest, California, the company operates research, development, manufacturing, and packaging facilities in California and Switzerland. For more information about ICL, visit To learn more about STAAR, visit Important Safety Information for the EVO Family of ICLs The EVO Visian ICL Lens is intended for the correction of moderate to high nearsightedness. EVO Visian ICL and EVO Visian TICL surgery is intended to safely and effectively correct nearsightedness between -3.0 D to -15.0 D, the reduction in nearsightedness up to -20.0 D and treatment of astigmatism from 1.0 D to 4.0 D. If patients have nearsightedness within these ranges, EVO Visian ICL surgery may improve distance vision without eyeglasses or contact lenses. Because the EVO Visian ICL corrects for distance vision, it does not eliminate the need for reading glasses, patients may require them at some point, even if they have never worn them before. Implantation of the EVO Visian ICL is a surgical procedure, and as such, carries potentially serious risks. Patients should discuss the risks with their eye care professional. Complications, although rare, may include need for additional surgical procedures, inflammation, loss of cells from the back surface of the cornea, increase in eye pressure, and cataracts. For additional information with potential benefits, risks and complications please visit Additional Information This press release may be deemed solicitation material in respect of the proposed acquisition of STAAR. A special stockholder meeting will be announced soon to obtain stockholder approval in connection with the proposed merger. STAAR expects to file with the SEC a proxy statement and other relevant documents in connection with the proposed merger. Investors of STAAR are urged to read the definitive proxy statement and other relevant materials carefully and in their entirety when they become available because they will contain important information about the Company and the proposed merger. Investors may obtain a free copy of these materials (when they are available) and other documents filed by STAAR with the SEC at the SEC's website at and at STAAR's website at No Offer or Solicitation This communication is for informational purposes only and is not intended to and does not constitute, or form part of, an offer, invitation or the solicitation of an offer or invitation to purchase, otherwise acquire, subscribe for, sell or otherwise dispose of any securities, or the solicitation of any vote or approval in any jurisdiction, pursuant to the proposed transaction or otherwise, nor shall there be any sale, issuance or transfer of securities in any jurisdiction in contravention of applicable law. Participants in the Solicitation Alcon, STAAR and certain of their respective directors, executive officers and other members of management and employees may be deemed to be participants in soliciting proxies from its stockholders in connection with the proposed merger. Information regarding Alcon's directors and executive officers is contained in Alcon's annual report on Form 20-F for its fiscal year ended December 31, 2024, which was filed with the SEC on February 25, 2025. Information regarding the persons who may, under the rules of the SEC, be considered to be participants in the solicitation of STAAR's stockholders in connection with the proposed merger will be set forth in STAAR's definitive proxy statement for its special stockholder meeting. Additional information regarding these individuals and any direct or indirect interests they may have in the proposed merger will be set forth in the definitive proxy statement when and if it is filed with the SEC in connection with the proposed merger. References Global Prevalence of Myopia and High Myopia and Temporal Trends from 2000 through 2050. Brien A Holden at al. Ophthalmology. 2016 May;123(5):1036-42. Connect with us on Facebook LinkedIn View source version on Contacts Alcon Investor Relations Daniel Cravens, Allen Trang+ 41 589 112 110 (Geneva)+ 1 817 615 2789 (Fort Worth) Alcon Media Relations Steven Smith+ 41 589 112 111 (Geneva)+ 1 817 551 8057 (Fort Worth) STAAR Investor & Media Relations Niko Liu, CFAUnited States: 626-303-7902 ext 3023Hong Kong: +852-6092-5076nliu@ investorrelations@ Connie Johnson+1 626 303 7902 (x-2207)cjohnson@

Analysis-Europe's old power plants to get digital makeover driven by AI boom
Analysis-Europe's old power plants to get digital makeover driven by AI boom

Yahoo

time22 minutes ago

  • Yahoo

Analysis-Europe's old power plants to get digital makeover driven by AI boom

By Forrest Crellin PARIS (Reuters) -Some of Europe's ageing coal and gas fired power plants can look forward to a more high-tech future as big tech players, such as Microsoft and Amazon, seek to repurpose them as data centres, with ready-made access to power and water. Companies such as France's Engie, Germany's RWE, and Italy's Enel are looking to benefit from a surge in AI-driven energy demand by converting old power sites into data centres and securing lucrative long-term power supply deals with their operators. The data centre option offers the utilities a way to offset the hefty costs of shutting down ageing power plants as well as potentially underwriting future renewable developments. Tech companies see these sites as a quick way to secure power grid connections and water cooling facilities, two big bottlenecks in the AI industry. "You have all the pieces that come together like ... water infrastructure and heat recovery," said Bobby Hollis, vice president for energy at Microsoft. Lindsay McQuade, EMEA energy director at Amazon , said she expected permitting for data centres to move faster at old sites, where a big chunk of infrastructure was already in place. Utilities can either lease the land or build and operate the centres themselves, securing long-term power contracts with tech firms, he said. The deals offer much more than just the sale of unused land as they include opportunities for stable, high-margin revenue, said Simon Stanton, head of Global Partnerships and Transactions at RWE. "It's more about the long-term relationship, the business relationship that you get over time that enables you to de-risk and underwrite your infrastructure investments," Stanton said. Most of EU's and Britain's 153 hard coal and lignite plants are set to close by 2038 to meet climate targets, joining the 190 plants that have closed since 2005, based on data from NGO Beyond Fossil Fuels, which campaigns to accelerate closure of coal-fired power stations. NEW REVENUE STREAMS The economics of data centre deals can be compelling for the utilities, which can negotiate a long-term power supply contract to underwrite future renewable developments. Tech firms are paying premiums of up to 20 euros per megawatt-hour for low-carbon power, said Gregory LeBourg, environmental program director at French data centre operator OVH. Data centre power demands can be anywhere from a couple hundred megawatts to a gigawatt or more. So the annual 'green premium' - the extra price paid for low-carbon electricity - on top of a base market price could potentially translate into a long-term contract worth hundreds of millions or even billions of euros, based on Reuters' calculations. One long-term option is to build an "energy park" and connect the data centre to a new renewable development, relying on the grid for emergencies, but this is a relatively new concept, industry sources said. Engie wants to double its installed renewable energy by 2030 from the current 46 GW. The group has identified 40 sites globally that it is marketing to data centre developers, including coal and gas plants that could be converted, said Sebastien Arbola, who runs the company's data centre business. One is the Hazelwood coal plant in Australia, which closed in 2017. He declined to disclose details of other sites, saying they are mostly in Europe. Other utilities, including Portugal's EDP, EDF, and Enel said they are also marketing old gas and coal sites for new data centre development. "It's business model diversification," said Michael Kruse, managing partner at consultancy Arthur D. Little. Utilities are creating a new type of business and also new revenue streams, he said. 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Britain's Drax is also seeking a partner to develop unused parts of an old coal site in Yorkshire, now partially converted to biomass. It offers access to unused water cooling equipment, said Richard Gwilliam, Drax's carbon programme director. Drax is offering a "behind-the-meter" deal where the power plant will provide direct power to the data centre and it can pull from the grid if necessary. EDF has also chosen developers for two sites at gas power plants in central and eastern France. Tech companies are willing to pay more for projects that can start up sooner as they vie for market share in a rapidly growing industry, said Sam Huntington, director of research at S&P Global Commodity Insights. "Speed to power is just the phrase we keep hearing over and over again," he said. Error in retrieving data Sign in to access your portfolio Error in retrieving data Error in retrieving data Error in retrieving data Error in retrieving data

Scaling Production AI: 20 Surprising Hurdles And How To Overcome Them
Scaling Production AI: 20 Surprising Hurdles And How To Overcome Them

Forbes

time24 minutes ago

  • Forbes

Scaling Production AI: 20 Surprising Hurdles And How To Overcome Them

Scaling AI from prototype to production is a major hurdle for many organizations. Even with skilled teams and powerful models, companies often hit unexpected bottlenecks—such as disjointed data pipelines, unclear ownership or low user trust—that slow or stall progress. To scale AI successfully, businesses need more than just technical expertise; they must invest in robust infrastructure, change management and cross-functional alignment. Below, members of Forbes Technology Council reveal common hurdles teams face when scaling production AI—and share practical strategies for overcoming them. 1. Instilling Digital Literacy And Trust Among Team Members A major bottleneck in scaling AI is organizational resistance due to fear and digital skill gaps. Many employees worry that AI will replace their roles or feel unprepared to use it. This often leads to low engagement and stalled adoption. To overcome this, companies must invest in AI literacy and upskilling. Involving staff early in the AI journey fosters trust, making scaling smoother. - Praveen Tomar, UK Civil Services (Ofgem) 2. Choosing The Right Problems To Tackle AI holds promise in enterprise restaurants—from predicting inventory to personalizing upsells. However, a common bottleneck isn't technical; it's misalignment between what's built and what drives value. Too often, teams chase flashy use cases without validating impact. Scaling AI starts with choosing the right problems and having the right data. - Peter Kellis, TRAY Forbes Technology Council is an invitation-only community for world-class CIOs, CTOs and technology executives. Do I qualify? 3. Providing Frontline Access One key bottleneck is providing direct access for the frontline workers who would benefit from it. Providing frontline workers with AI solutions to efficiently and effectively complete their tasks is critical in today's landscape, where time is of the essence. - Mike Zachman, Zebra Technologies Corporation 4. Building Trustworthy Data Architecture Fragmented data architectures fragment business context. Without integrated enterprise knowledge, AI lacks organizational understanding. Success requires a trusted data architecture that's operationally simple yet preserves business meaning. - Louis Landry, Teradata 5. Avoiding Prompt Injection And Tool Misuse Prompt injection and tool misuse are critical bottlenecks. Attackers can trick LLMs into leaking sensitive data, performing unauthorized actions or amplifying these to widen impact. This slows deployment and can lead to costly breaches. You can mitigate risk with the same security best practices that you use elsewhere in the organization: least privilege, sandboxing, audits and adversarial testing. - Willem Delbare, Aikido 6. Managing AI-Generated Content Overload AI will generate more content than existing review and approval processes are designed to handle. Companies will need to decide how to proceed—they can either accept the risk, dramatically slowing adoption, or find and/or build tools to help them manage it. - Larry Bradley, SolasAI 7. Identifying And Managing ML Pipeline Cost And Performance Issues Companies often overlook MLOps when they take on AI-related development. ML pipelines can have very different cost and performance challenges than traditional development domains. Understanding the true unit cost of model performance is essential and can mean the difference between a model that scales well and one that doesn't. - Siamak Baharloo, Labviva 8. Linking AI Spend To Business Value One big bottleneck? The CFO calling out the inference cost line on the P&L. If teams can't clearly link AI costs to business value, there's a real risk that projects will stall. The solution? An AI Command Room. Start by building a clear business case tied to at least one normalized metric, such as labor dollars saved through AI agents and automation. Then, track and report impact—from hypothesis to daily execution. - Matt Kesby, Multiplai Tech 9. Establishing Shared Data Definitions As enterprises deploy agentic AI, agents make decisions based on data no one fully trusts. In pilots, humans catch issues. At scale, autonomous systems pull from disconnected sources with conflicting rules, and small cracks become major failures. The issue isn't the model; it's the lack of data trust. Scaling AI requires shared definitions and automated checks to ensure a reliable foundation. - Jay Limburn, Ataccama 10. Grounding Data In Real-Time, Trusted Context A key bottleneck in scaling AI is context fragmentation—models can't reason effectively without access to clean, connected and secure organizational data. Grounding data in real-time, trusted context is the real challenge. The fix is better infrastructure: unified knowledge layers, privacy-preserving compute and retrieval pipelines that align AI with the right data. - Regan Peng, PINAI 11. Addressing Data Lineage And Quality Debt One unexpected bottleneck is data lineage and quality debt. Many organizations assume that once a model is trained and performs well in testing, scaling it into production is mostly an engineering and computing problem. In reality, the biggest bottleneck often emerges from inconsistent, incomplete or undocumented data pipelines—especially when legacy systems or siloed departments are involved. - Sandeep Uthra, OneAZ Credit Union 12. Working With Outdated Infrastructure A bottleneck would be inadequate data infrastructure, which can be overcome by investing in modern, scalable data platforms and robust engineering practices. Companies should be establishing robust data governance practices and centralized data infrastructure early in the development lifecycle. - Nazih Chamtie, KMicro Tech, Inc. 13. Managing Model Drift Even though data quality is an obvious bottleneck, when we scaled AI in production, I primarily expected challenges with data and infrastructure. However, what caught us off guard was model drift. For example, in finance, market shifts rendered our fraud models stale. In healthcare, evolving patient data skewed predictions. Real-time monitoring and retraining turned out to be just as critical as building the models. - Dr. Suresh Rajappa, KPMG LLP 14. Overcoming Resistance To AI Integration Change management within the existing user experience is a significant challenge when scaling AI. While AI has enormous potential to enhance user experience, effective integration requires more than technical implementation. Organizations can proactively address this issue by increasing user adoption, reducing resistance and unlocking AI's full transformative potential. - Shivaprakash S Nagaraj, Digit7 15. Struggling To Find Skilled Architects And Operators Designing and building infrastructures that support AI initiatives requires a different set of skills. While many current IT professionals will get up to speed over time, there are significant nuances that come with AI that they may have never experienced before. Struggling to find skilled infrastructure architects and operators who already understand these nuances will be the reality for a few years. - Mike Wong, Accton Technology 16. Developing A Single Source Of Truth AI can be hindered by a lack of data access, data silos, data quality issues, missing context and so on. A lack of a single source of truth is also a common issue—especially if data connections are intermittent and complex—and AI models need to be run locally. Thinking strategically about the desired business outcomes and implementing a data fabric will improve data management and help scale AI end-to-end. - Heiko Claussen, Aspen Technology, Inc. 17. Identifying And Patching Security Gaps Security is the most significant challenge, because LLMs can't be controlled. Even foundational model providers' system prompts and training instructions have leaked. Strengthening AI security requires identifying potential vulnerabilities and testing against them, but we do not yet have an exhaustive list of those vulnerabilities, as AI systems remain a black box. - Rohit Kapoor, Tekmonks 18. Connecting AI Outputs To Decision-Making Processes A major bottleneck is the lack of integration between AI models and core business workflows. Even the best models fail to deliver value if their outputs don't connect to decision-making tools or processes. You can overcome this by embedding AI via APIs, aligning with existing systems and designing with end users to ensure seamless adoption and continuous feedback loops. - Motasem El Bawab, N3XT Sports 19. Detecting Performance Degradation Companies can build decent AI models but struggle to scale them due to poor production monitoring and deployment capabilities. Unlike deterministic code, where 2 + 2 always equals 4, AI models produce variable outputs, making it hard to detect performance degradation. Companies can overcome this by implementing robust MLOps pipelines with continuous monitoring, A/B testing, and automated alerts for model drift detection. - Mia Millette, Skyline Technology Solutions 20. Ensuring Organizational Alignment Accelerating AI initiatives without addressing data quality, readiness and strategic alignment will undoubtedly result in significant roadblocks. To scale successfully, organizations must prioritize use cases based on business impact, ensure data is properly prepared, and tightly align each initiative with clear, measurable outcomes. - Sean Nathaniel, DryvIQ

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