Core Insights - The ADP 2026 HR Trends Guide highlights the shift towards an AI-driven workplace, emphasizing a skills-based approach to align talent with organizational goals [1][4][10] - The report stresses the importance of HR-IT collaboration, responsible AI governance, and transparency in shaping the future of work [1][5][6] Skills-Based Job Design - Organizations are assessing their skills inventory and strategically redesigning roles to align talent with business needs as AI transforms the workplace [4] - 84% of large organizations believe AI can streamline processes without replacing employees, with 76% of midsized and 73% of small organizations sharing this view [4] AI Integration and Employee Engagement - AI is reframed as a collaborative partner, empowering employees to innovate and engage more fully with their work [4][6] - Successful AI adoption requires intentional training, hands-on experimentation, and leadership that models continual learning [4] Compliance and Regulatory Landscape - Pay transparency requirements are expanding, particularly in the EU, necessitating clearer information on pay, advancement, and gender gaps by 2026 [6] - Organizations face multijurisdictional compliance challenges, requiring a consistent approach to navigate varying local, state, and federal laws [6] Agentic AI in HR Operations - Agentic AI is emerging as a core capability in Human Capital Management (HCM), streamlining HR operations through automation and proactive insights [6] - 20% of small businesses, 50% of midsized, and two-thirds of large companies report having a governance process for generative AI [6] HR-IT Collaboration - The reliance between HR and IT is increasing as AI reshapes the workplace, necessitating close collaboration for effective and responsible work delivery [6][7] - IT's expertise in technology management is becoming crucial for HR leaders, while HR provides insights on the human impact of these tools [7]

Key Points Western Digital's business is prone to boom and bust cycles. But right now, business is booming. Agentic AI will likely be a material driver for memory products in the coming years. 10 stocks we like better than Western Digital › I have a small obsession with tracking the best-performing stocks in the S&P 500. I want to know why they were winners, so that I can better identify future winners. Among stocks that were in the S&P 500 index for the entire year, Nvidia was the best performer ...

30 Agentic AI terms AI engineers should know: https://t.co/uOnNZEXsu0 ...

Core Insights - The era of Agentic AI has begun, marking a transition from AI as a tool to AI as a partner, with 79% of companies already implementing related applications, although 62% remain in the early stages of adoption [5][7][8] - Digital investment intentions have significantly recovered, with 65% of companies planning to increase their digital investments, indicating a clear strategic divergence in the AI era [27][31] - The value focus of AI has shifted from cost reduction to enhancing office efficiency and expanding business boundaries, with 97% of companies applying AI and 56% reporting significant value generation [35][38][40] Group 1: Agentic AI - Agentic AI represents a new era where AI can autonomously set goals and execute complex tasks, reshaping workflows and organizational structures [5] - Companies face challenges in selecting scenarios, matching technologies, talent reserves, and data governance while implementing AI [8][10] - The most suitable applications for Agentic AI include knowledge base Q&A and customer service Q&A due to their clear tasks and verifiable results [14] Group 2: Digital Investment Trends - The distribution of digital investment is characterized by a "dumbbell" pattern, with some companies cautiously reducing spending while others aggressively invest in AI transformation [27][31] - The median digital investment as a percentage of revenue for surveyed companies remains stable at 1%-3%, while leading companies invest 3%-5% [27] - A notable 12% of companies expect their digital investments to increase by over 50% compared to the previous year [27] Group 3: Value Creation through AI - The driving forces behind AI adoption are evolving, with a focus on enhancing operational efficiency and expanding business opportunities [35][38] - AI is becoming a core productivity driver across the entire production and operation chain, fundamentally reshaping business logic and collaboration models [35][38] - The rise of open-source models is facilitating a more diverse AI ecosystem, with Chinese companies playing a significant role [40] Group 4: AI Model Advancements - AI models have achieved breakthroughs in performance, cost, and speed, significantly enhancing the economic viability and accessibility of AI services [44] - The proportion of companies deploying AI through self-deployment and training small models has increased, while reliance on external vendors has decreased [49] - The rapid advancement of AI technology is enabling more companies to customize and deploy AI solutions tailored to their specific needs [46] Group 5: AI Empowerment and Challenges - AI is breaking down barriers in knowledge and technology, leading to the emergence of "super individuals" capable of integrating AI into their workflows [51] - The rise of AI also brings security risks, with fraud and misinformation becoming significant threats, necessitating robust data governance frameworks [57] - Companies must prioritize data security and risk management as integral parts of their AI strategy to mitigate potential losses [57] Group 6: Organizational Transformation - Organizations are transitioning towards a more streamlined and intelligent structure, with a focus on human-AI collaboration [60][63] - The demand for creativity and innovative thinking is increasing, with companies recognizing these as key competencies in the AI environment [61] - The role of AI agents is expanding beyond tools to become integral parts of the workforce, requiring new management approaches [63][65]

This is interesting because we're going from the domain of aentic AI and we're trying to take it to how consumers already use search >> marry them in the context of retail. >> How does it work and why is it important. >> Yeah.So, Agentic tech is, you know, relatively new and we're really focusing on bringing agentic AI for consumer problems that really matter to consumers. And so, for example, taking the tedious parts of shopping and having agentic AI, which is AI that does things on behalf of the user. So ...

Core Insights - NICE reported adjusted earnings of $3.18 per share for Q3 2025, exceeding the Zacks Consensus Estimate by 0.32% and reflecting a 10% year-over-year increase [1] - Non-GAAP revenues reached $732 million, surpassing the consensus mark by 0.56% and increasing 6% year over year, primarily driven by the strength of its cloud business and customer base expansion [1][8] Revenue Breakdown - Revenues in the Americas were $618 million, up 5% year over year; EMEA revenues were $74 million, up 7% year over year; APAC revenues increased 19% year over year to $40 million [2] - Cloud revenues constituted 76.9% of total revenues at $562.9 million, beating the Zacks Consensus Estimate by 0.64% and rising 13% year over year [3] - Service revenues accounted for 18.9% of total revenues at $138.7 million, missing the consensus mark by 0.40% and declining 7.4% year over year [3] - Product revenues made up 4.1% of total revenues at $30.4 million, exceeding the consensus mark by 3.55% but decreasing 24.1% year over year [4] Operating Performance - Non-GAAP gross margin contracted 120 basis points to 69.9% in the reported quarter [5] - Research and development expenses as a percentage of revenues decreased 90 basis points year over year to 12.4% [5] - Non-GAAP operating margin contracted 50 basis points year over year to 31.5% [6] - Non-GAAP EBITDA margin contracted 40 basis points to 34.7% [6] Cash Flow and Balance Sheet - As of September 30, 2025, NICE had cash and cash equivalents of $455.9 million, down from $1.63 billion as of June 30, 2025 [9] - Cash flow from operations in Q3 was $190.5 million compared to $61.32 million in the prior quarter [9] - $40.6 million was allocated for share repurchase in Q3 2025 [9] Future Guidance - NICE projects non-GAAP revenues between $2.93 billion and $2.94 billion for the full year 2025, implying 7% year-over-year growth at the midpoint [10] - Non-GAAP earnings are estimated to be between $12.18 and $12.32 per share, suggesting 10% year-over-year growth at the midpoint [10]

Core Insights - The company has launched SARA™ ASSIST, an extension of its SARA platform, aimed at enhancing remote video monitoring and operations in GSOC and SOC environments [1][3][4] - SARA ASSIST integrates agentic AI into operator workflows, improving efficiency without fully automating the monitoring process [3][5][6] Product Features - SARA ASSIST provides real-time verification, notification, and documentation capabilities, allowing operators to manage incidents more effectively [1][3] - The platform complements existing SARA offerings, including VERIFIED, LITE, AGENT, and EDGE, and is designed to facilitate a gradual transition to full automation [6][5] Market Position - The company is positioned to redefine the $50 billion security and guarding services industry through its innovative AI-driven solutions, which can reduce costs for businesses by 35%-80% compared to traditional manned security [8][12] - The company has a prospective sales pipeline that includes over 35 Fortune 500 companies, indicating strong market interest and potential for recurring revenue [11] Leadership and Expertise - The company is led by experienced professionals in the security services industry, including CEO Steve Reinharz, who has a strong background in security technology and innovation [10][12] - The leadership team includes individuals with extensive expertise in law enforcement and robotics, enhancing the company's capability to deliver effective solutions [10]

Group 1 - The focus of technology has shifted from Generative AI (GenAI) to Agentic AI (A-AI), marking a significant change in how software interacts with the world [1][3] - Agentic AI systems are capable of reasoning, planning, and executing multi-step goals autonomously, representing a complete architectural shift in software functionality [4] - Traditional enterprise systems like ERP are designed as systems of record, while A-AI is designed to be a system of action, indicating a transformative approach to enterprise technology [4]

Core Insights - The partnership between Ascertain and The Oncology Institute aims to create "near-touchless" administrative workflows to reduce manual interactions between providers and payers [1][2] Group 1: Partnership and Technology - Ascertain's Unified Payer Portal (UPP) is an AI-powered automation module designed to streamline payer-related tasks for outpatient oncology visits [2] - The implementation of the UPP was completed in just eight weeks, showcasing the adaptability of Ascertain's technology and the strength of the partnership [3] Group 2: Operational Efficiency - Since the deployment in September 2025, the automation has reduced authorization submission time by over 80% at pilot sites, saving hundreds of staff hours weekly [4] - The initiative is projected to generate up to $2 million in operating expense savings in 2026 as it scales across all authorization types [4] Group 3: Company Background - Ascertain specializes in automating complex administrative workflows in healthcare using agentic AI, replacing manual tasks with intelligent automation [6] - The Oncology Institute, founded in 2007, focuses on delivering value-based cancer care and operates over 100 clinics across five states, serving approximately 1.9 million patients [7]

Core Insights - Cash App is introducing Moneybot, an advanced financial services chatbot that can perform complex tasks such as creating savings plans and evaluating spending habits, unlike traditional bank chatbots that handle routine tasks [2][6][8] - Moneybot utilizes "agentic" AI technology, allowing it to act on behalf of users, which marks a significant evolution in chatbot capabilities within the financial services sector [3][5] - The introduction of Moneybot reflects a shift in the banking industry, with Cash App taking a proactive approach while traditional banks remain cautious due to concerns over liability and data security [6][7] Company Developments - Cash App plans to roll out Moneybot this winter, aiming to enhance user interaction and streamline financial management within its app [2][8] - The chatbot will analyze customer transactions and provide personalized recommendations, making it a central feature for user engagement in the future [8] Industry Trends - The rise of "agentic" AI is prompting discussions about the implications for customer data security and potential liabilities, as seen in Amazon's lawsuit against Perplexity for alleged misuse of AI shopping agents [5][6] - Other companies like Amazon and Walmart are also developing similar AI capabilities, indicating a broader trend towards integrating advanced AI in consumer interactions [4]