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nostalgebraist · 2 years ago

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@oakfern replied to your post “it's going to be fun to watch the realization...”:

i feel like this is going to play out very similarly to voice assistants. there was a huge boom in ASR research, the products got a lot of hype, and they actually sold decently (at least alexa did). but 10 years on, they've been a massive failure, costing way more than they ever made back. even if ppl do think chatbot search engines are exciting and cool, it's not going to bring in more users or sell more products, and in the end it will just be a financial loss

(Responding to this a week late)

I don't know much about the history of voice assistants. Are there any articles you recommend on the topic? Sounds interesting.

ETA: Iater, I found and read this article from Nov 2022, which reports that Alexa and co. still can't turn a profit after many years of trying.

But anyway, yeah... this is why I don't have a strong sense of how widespread/popular these "generative AI" products will be a year or two from now. Or even five years from now.

(Ten years from now? Maybe we can trust the verdict will be in at that point... but the tech landscape of 2033 is going to be so different from ours that the question "did 'generative AI' take off or not?" will no doubt sound quaint and irrelevant.)

Remember when self-driving cars were supposed to be right around the corner? Lots of people took this imminent self-driving future seriously.

And I looked at it, and thought "I don't get it, this problem seems way harder than people are giving it credit for. And these companies show no signs of having discovered some clever proprietary way forward." If people asked me about it, that's what I would say.

But even if I was sure that self-driving cars wouldn't arrive on schedule, that didn't give me much insight into the fate of "self-driving cars," the tech sector meme. It wasn't like there was some specific deadline, and when we crossed it everyone was going to look up and say "oh, I guess that didn't work, time to stop investing."

The influx of capital -- and everything downstream from it, the trusting news stories, the prominence of the "self-driving car future" in the public mind, the seriousness which it was talked about -- these things went on, heedless of anything except their own mysterious internal logic.

They went on until . . . what? The pandemic, probably? I actually still don't know.

Something definitely happened:

In 2018 analysts put the market value of Waymo LLC, then a subsidiary of Alphabet Inc., at $175 billion. Its most recent funding round gave the company an estimated valuation of $30 billion, roughly the same as Cruise. Aurora Innovation Inc., a startup co-founded by Chris Urmson, Google’s former autonomous-vehicle chief, has lost more than 85% since last year [i.e. 2021] and is now worth less than $3 billion. This September a leaked memo from Urmson summed up Aurora’s cash-flow struggles and suggested it might have to sell out to a larger company. Many of the industry’s most promising efforts have met the same fate in recent years, including Drive.ai, Voyage, Zoox, and Uber’s self-driving division. “Long term, I think we will have autonomous vehicles that you and I can buy,” says Mike Ramsey, an analyst at market researcher Gartner Inc. “But we’re going to be old.”

Whatever killed the "self-driving car" meme, though, it wasn't some newly definitive article of proof that the underlying ideas were flawed. The ideas never made sense in the first place. The phenomenon was not really about the ideas making sense.

Some investors -- with enough capital, between them, to exert noticable distortionary effects on entire business sectors -- decided that "self-driving cars" were, like, A Thing now. And so they were, for a number of years. Huge numbers of people worked very hard trying to make "self-driving cars" into a viable product. They were paid very well to do. Talent was diverted away from other projects, en masse, into this effort. This went on as long as the investors felt like sustaining it, and they were in no danger of running out of money.

Often the "tech sector" feels less like a product of free-market incentives than it does like a massive, weird, and opaque public works product, orchestrated by eccentrics like Masayoshi Son, and ultimately organized according to the aesthetic proclivities and changing moods of its architects, not for the purpose of "doing business" in the conventional sense.

Gig economy delivery apps (Uber Eats, Doordash, etc.) have been ubiquitous for years, and have reported huge losses in every one of those years.

This entertaining post from 2020 about "pizza arbitrage" asks:

Which brings us to the question - what is the point of all this? These platforms are all losing money. Just think of all the meetings and lines of code and phone calls to make all of these nefarious things happen which just continue to bleed money. Why go through all this trouble?

Grubhub just lost $33 million on $360 million of revenue in Q1.

Doordash reportedly lost an insane $450 million off $900 million in revenue in 2019 (which does make me wonder if my dream of a decentralized network of pizza arbitrageurs does exist).

Uber Eats is Uber's "most profitable division” 😂😂. Uber Eats lost $461 million in Q4 2019 off of revenue of $734 million. Sometimes I need to write this out to remind myself. Uber Eats spent $1.2 billion to make $734 million. In one quarter.

And now, in February 2023?

DoorDash's total orders grew 27% to 467 million in the fourth quarter. That beat Wall Street’s forecast of 459 million, according to analysts polled by FactSet. Fourth quarter revenue jumped 40% to $1.82 billion, also ahead of analysts’ forecast of $1.77 billion.

But profits remain elusive for the 10-year-old company. DoorDash said its net loss widened to $640 million, or $1.65 per share, in the fourth quarter as it expanded into new categories and integrated Wolt into its operations.

Do their investors really believe these companies are going somewhere, and just taking their time to get there? Or is this more like a subsidy? The lost money (a predictable loss in the long term) merely the price paid for a desired good -- for an intoxicating exercise of godlike power, for the chance to reshape reality to one's whims on a large scale -- collapsing the usual boundary between self and outside, dream and reality? "The gig economy is A Thing, now," you say, and wave your hand -- and so it is.

Some people would pay a lot of money to be a god, I would think.

Anyway, "generative AI" is A Thing now. It wasn't A Thing a year ago, but now it is. How long will it remain one? The best I can say is: as long as the gods are feeling it.

#oakfern #ai tag

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mezzopieno-news · 8 months ago

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CROLLA IL COSTO DELLE BATTERIE ELETTRICHE E DELLE AUTO

Le batterie elettriche per auto sono passate nell’ultimo anno dall’essere in scarsità ad essere in eccesso, questo sta portando i prezzi a scendere drasticamente. Le nuove batterie a rapida ricarica sono sempre più piccole e durature e la loro riciclabilità è diventata la nuova frontiera su cui i produttori si stanno conquistando le nuove quote di mercato.

Il più grande produttore di batterie al mondo Contemporary Amperex Technology ha visto le quotazioni delle proprie batterie al litio scendere di circa il 50% mentre la casa automobilistica Leapmotor ha affermato che i prezzi potranno scendere quest’estate dal 60% al 64%. Il mercato delle auto elettriche in forte crescita sta guidando la rapida introduzione di nuove tecnologie e la diffusione di batterie sempre più performanti e veloci da ricaricare. I grandi gruppi automobilistici mondiali inoltre stanno sviluppando piattaforme dedicate esclusivamente alle auto elettriche che abbattono i costi di produzione in maniera significativa. Le nuove auto sono sempre di più costruite in sezioni come un unico pezzo, tecnica che si traduce in un risparmio di circa il 20% rispetto all’attuale sistema di produzione.

Le batterie sono l’elemento più costoso di un’auto elettrica, rappresentando il 30-40% del prezzo di produzione. Un’analisi di Gartner Inc., multinazionale che si occupa di ricerca e analisi nel campo della tecnologia, ha previsto che nel 2027 si assisterà al pareggio dei costi delle auto elettriche rispetto a quelle endotermiche, per poi vedere il costo delle prime scendere al punto da permettere la graduale obsolescenza delle auto con motore a scoppio.

___________________

Fonte: CnEVPost; Gartner; foto di ArtisticOperations Pixabay Needpix

VERIFICATO ALLA FONTE | Guarda il protocollo di Fact checking delle notizie di Mezzopieno

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#mezzopieno #tgbuonenotizie #buonenotizie #buonenotiziedalmondo

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pollicinor · 1 year ago

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Recessione incoming

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impact-newswire · 14 days ago

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Glean Named an AI Cool Vendor in the 2024 Gartner Cool Vendors for Digital Workplace Applications

Gartner report reinforces Glean’s momentum and advancement of Generative AI Press Release – November 08, 2024 – PALO ALTO, Calif. – Work AI leader Glean today announced it has been named a Cool Vendor in the 2024 Cool Vendors in Digital Workplace Applications1 report by Gartner, Inc. “Glean is unique in its ability to bring the power of AI to the daily work of everyone in an organization,…

#AI #Artificial Intelligence #Software Development

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me-amaraja · 21 days ago

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Facade Market Insights: Regional Analysis and Key Players

Facade Market Growth Strategic Market Overview and Growth Projections

The global facade market size was valued at USD 244.3 billion in 2022. It is estimated to reach USD 409.3 billion by 2031, growing at a CAGR of 5.9% during the forecast period (2023–2031).

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Competitive Landscape

Some of the prominent key players operating in the Facade Market are

Bouygues

Hochtief

Skanska

Norsk Hydro ASA

Gartner (Permasteelisa Group)

HansenGroup

Enclos

Aluplex

Fundermax

YKK AP Inc.

Rockpanel Group

Schuco International (OTTO FUCHS KG)

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Market Highlights:

A company's revenue and the applications market are used by market analysts, data analysts, and others in connected industries to assess product values and regional markets.

But not limited to: reports from corporations, international Organization, and governments; market surveys; relevant industry news.

Examining historical market patterns, making predictions for the year 2022, as well as looking forward to 2032, using CAGRs (compound annual growth rates)

Historical and anticipated data on demand, application, pricing, and market share by country are all included in the study, which focuses on major markets such the United States, Europe, and China.

Apart from that, it sheds light on the primary market forces at work as well as the obstacles, opportunities, and threats that suppliers face. In addition, the worldwide market's leading players are profiled, together with their respective market shares.

Goals of the Study

What is the overall size and scope of the Facade Market market?

What are the key trends currently influencing the market landscape?

Who are the primary competitors operating within the Facade Market market?

What are the potential growth opportunities for companies in this market?

What are the major challenges or obstacles the market is currently facing?

What demographic segments are primarily targeted in the Facade Market market?

What are the prevailing consumer preferences and behaviors within this market?

What are the key market segments, and how do they contribute to the overall market share?

What are the future growth projections for the Facade Market market over the next several years?

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About Straits Research

Straits Research is dedicated to providing businesses with the highest quality market research services. With a team of experienced researchers and analysts, we strive to deliver insightful and actionable data that helps our clients make informed decisions about their industry and market. Our customized approach allows us to tailor our research to each client's specific needs and goals, ensuring that they receive the most relevant and valuable insights.

Email: [email protected]

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#Facade Market Market #Facade Market Market Share #Facade Market Market Size #Facade Market Market Research #Facade Market Industry #What is Facade Market?

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livewalksite · 25 days ago

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Gartner, Inc. (IT): Among The 8 Best Information Technology Services Stocks to Invest in Now - Insider Monkey - https://live-walk.site/2024/11/gartner-inc-it-among-the-8-best-information-technology-services-stocks-to-invest-in-now-insider-monkey/

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news365timesindia · 28 days ago

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[ad_1] The global semiconductor market is on track to experience substantial growth in the coming years, with total revenue expected to reach USD 630 billion in 2024–a 19 per cent increase from the previous year. According to a recent report by Gartner, Inc., this upward trajectory is projected to continue, with revenue anticipated to climb to USD 717 billion in 2025, marking an additional 14 per cent growth. The report also highlighted that this growth follows a challenging period in 2023 when the semiconductor market declined. However, double-digit growth rates in 2024 and 2025 signal a robust rebound, primarily driven by a surge in demand for AI-related semiconductors and a recovery in electronics production. “The growth is driven by a continued surge in AI-related semiconductor demand and recovery in electronic production, while demand from the automotive and industrial sectors continues to be weak,” said Rajeev Rajput, Senior Principal Analyst at Gartner. The report also noted that the memory market and graphics processing units (GPUs) are expected to significantly drive semiconductor revenue in the near term. Specifically, memory market revenue is forecasted to grow by 20.5 percent in 2025, reaching USD 196.3 billion. This growth will be influenced by a sustained undersupply of memory components in 2024, which is expected to drive NAND flash memory prices up by 60 percent this year. While prices are anticipated to soften by about 3 per cent in 2025, NAND flash revenue is forecasted to reach USD 75.5 billion, representing a 12 per cent increase from 2024. DRAM, another crucial memory segment, is also predicted to experience a recovery, with revenues expected to reach USD 115.6 billion in 2025, up from USD 90.1 billion in 2024, as per the report. This growth is supported by an easing undersupply, increased high-bandwidth memory (HBM) production, and rising demand for double data rate 5 (DDR5) technology. The GPU market, which has become essential for the training and developing AI models, is also projected to grow significantly. After a dip in 2023, GPU revenue is set to rebound, with an expected 27 per cent increase in 2025, bringing it to USD 51 billion. The report noted that demand for HBM, a specialised memory solution for high-performance AI servers, is also seeing a steep rise. “Vendors are investing significantly in HBM production and packaging to match next-generation GPU/AI accelerator memory requirements,” said George Brocklehurst, VP Analyst at Gartner. Overall, the semiconductor industry is poised for a promising future, with AI and memory technology serving as significant catalysts for growth in the coming years. [ad_2] Source link

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news365times · 28 days ago

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procurement-insights · 1 month ago

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Will a Gartner representative delete another one of my comments in which I ask a fair question?

What is the difference between Agentic AI and Agent-based AI models?

The following is the link to Gartner’s recent LinkedIn post to which I posed the following fair and well-researched question/comment: Here is the comment I made on the Globality, Inc. post that shared the above, specifically referencing Point #1 regarding Agentic AI: What is the difference between Agentic AI and Agent-based modeling? By doubling down on technology, is Gartner leading us astray?…

#Agent-Based (AI) Model #Agentic AI #Gartner #procurement #procuretech #supply chain

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yantainc · 2 months ago

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Bridging the Skill Gap: Training New Employees | Yantra Inc.

In the fast-paced world of business, the importance of nurturing talent cannot be overstated. As an HR professional, I’ve witnessed firsthand the challenges organizations face in recruiting and training new employees, especially mid-level managers who can take up to six months to reach a break-even point. The costs associated with hiring and training can be significant, making it imperative for companies to explore alternative strategies.

In the dynamic landscape of business, characterized by shifts in technology and consumer demands, companies must adapt to stay relevant. As an HR professional, it is my responsibility to ensure that the workforce is equipped with the necessary skills to meet changing requirements. This is where upskilling and reskilling come into play.

By investing in the development of their workforce, organizations can fill skill gaps, keep employees motivated, and foster loyalty. Skilled and adaptable employees not only contribute to the stability and goodwill of the organization but also reduce the time and expenses associated with hiring and training new personnel.

What is upskilling and reskilling?

Upskilling involves enhancing or acquiring new skills within an employee’s current area of expertise, while reskilling prepares employees for entirely new roles or technologies. Both strategies are essential for employee development and self-improvement, providing a pathway for continuous growth and advancement.

But why is bridging the skill gap necessary?

In today’s competitive market, adaptability is key to survival. Investing in upskilling and reskilling not only prepares businesses to handle rapid developments but also showcases forward-thinking leadership. Ultimately, the success of a company depends on its talented employees, who drive client relationships, manage technologies, and contribute to achieving growth objectives.

With the increasing prevalence of new technologies like artificial intelligence (AI), every aspect of business is being impacted. As per Gartner, 76% of HR leaders believe that if their organization does not adopt and implement AI solutions, in the next 12 to 24 months, they will be lagging in organizational success compared to those that do. For instance, AI is revolutionizing HR practices, from talent acquisition to workforce planning. As an HR professional, I believe embracing these advancements and redefining our talent management approach is essential.

How to bridge the skill gap?

To bridge the skill gap effectively, organizations must adopt a variety of strategies, including creating development plans tailored to individual skill sets, offering in-house training, collaborating with educational institutions, and supporting certification programs. Integrating learning into the workflow with real-time feedback and recommendations can enhance engagement and efficiency.

However, challenges in upskilling and reskilling exist, such as resistance to change and lack of motivation. It’s essential to engage employees through various channels, including offline training and mentorship programs, to overcome these challenges.

By embracing innovative approaches, organizations can empower their workforce to thrive in an ever-changing professional landscape. Bridging the skill gap is not just a necessity; it’s a strategic imperative for HR professionals like myself, driving innovation and growth in the process.

To Read Full Blog Visit- Bridging the Skill Gap: Training New Employees | Yantra Inc.

#Bridging the Skill Gap: Training

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crestcom · 6 months ago

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The Future of Leadership: Leveraging Artificial Intelligence for Strategic Decision-Making

In today's rapidly evolving business landscape, the integration of artificial intelligence (AI) into leadership practices has become imperative for organizations seeking to maintain a competitive edge. From enhancing strategic decision-making to optimizing operational efficiency, AI is revolutionizing the way leaders approach their roles. In this comprehensive guide, we delve into the various facets of leveraging AI for strategic decision-making and explore the future of leadership in the digital age.

Introduction to Leadership with AI

As organizations strive to adapt to an increasingly digitalized world, the role of AI in leadership has garnered significant attention. By leveraging AI technologies, leaders can harness vast amounts of data to gain valuable insights, streamline processes, and drive innovation. From predictive analytics to natural language processing, AI offers a plethora of tools that empower leaders to make informed decisions and navigate complex business challenges with agility.

Trending Industry Stats:

According to a report by Gartner, 85% of AI projects fail to deliver on their intended objectives due to a lack of clear goals and alignment with business needs.

Research from McKinsey & Company indicates that AI-driven organizations are 33% more likely to outperform their peers in terms of revenue growth.

Insights on Top Performers:

Amazon is a prime example of a company that has successfully integrated AI into its leadership practices. Through initiatives such as Alexa and Amazon Web Services (AWS), the tech giant leverages AI to enhance customer experiences, optimize supply chain management, and drive innovation.

Google's parent company, Alphabet Inc., is renowned for its AI-driven approach to leadership. From personalized search algorithms to self-driving cars, Alphabet harnesses AI to fuel its diverse portfolio of products and services.

The Role of AI in Strategic Decision-Making

In the realm of strategic decision-making, AI serves as a powerful ally for leaders seeking to navigate uncertainty and capitalize on opportunities. By analyzing vast datasets in real-time, AI algorithms can identify patterns, detect trends, and predict future outcomes with unprecedented accuracy. This enables leaders to make data-driven decisions that are grounded in insights rather than intuition, thereby enhancing the likelihood of success.

Trending Industry Stats:

A survey conducted by PwC found that 74% of executives believe that AI will be fundamental in helping their organizations gain a competitive advantage.

According to a study by IBM, companies that effectively leverage AI for strategic decision-making experience an average revenue increase of 14%.

Insights on Top Performers:

Netflix is renowned for its data-driven approach to content creation and distribution. By leveraging AI algorithms to analyze viewer preferences and behaviors, Netflix produces highly personalized recommendations, driving customer engagement and retention.

Tesla, under the leadership of Elon Musk, has embraced AI to revolutionize the automotive industry. With features such as Autopilot and Full Self-Driving (FSD) capabilities, Tesla vehicles utilize AI to enhance safety, efficiency, and overall driving experience.

Implementing AI-Driven Leadership Practices

The successful implementation of AI-driven leadership practices requires a strategic approach and a commitment to organizational transformation. From fostering a culture of innovation to investing in talent development, leaders must take proactive steps to ensure that AI initiatives align with business objectives and deliver tangible value.

Trending Industry Stats:

Deloitte reports that 91% of business leaders believe that AI is essential for remaining competitive in today's market.

A study by MIT Sloan Management Review found that organizations that effectively integrate AI into their operations are 1.5 times more likely to experience revenue growth.

Insights on Top Performers:

Microsoft is at the forefront of AI integration in leadership, with initiatives such as Azure AI and Microsoft Dynamics 365. By providing AI-powered solutions for businesses across various industries, Microsoft empowers leaders to drive innovation and achieve strategic objectives.

IBM Watson, IBM's AI platform, offers a suite of tools and services designed to assist leaders in decision-making, risk management, and resource optimization. Through applications in healthcare, finance, and beyond, IBM Watson showcases the transformative potential of AI in leadership.

Overcoming Challenges and Pitfalls

While AI presents numerous opportunities for leaders, it also poses unique challenges and pitfalls that must be addressed. From ethical considerations to data privacy concerns, leaders must navigate a complex landscape of risks to maximize the benefits of AI-driven decision-making.

Trending Industry Stats:

A survey by EY found that 56% of consumers are concerned about the ethical implications of AI, such as bias and privacy issues.

The World Economic Forum identifies cybersecurity threats as a top concern for organizations adopting AI, with 61% of executives citing cybersecurity as a significant risk.

Insights on Top Performers:

Facebook has faced scrutiny for its handling of user data and privacy concerns related to AI algorithms. Despite challenges, the social media giant continues to invest in AI research and development to enhance user experiences and drive innovation.

Airbnb employs AI to optimize pricing algorithms and enhance user recommendations. By leveraging AI-driven insights, Airbnb empowers hosts to maximize their earning potential while providing guests with personalized travel experiences.

Maximizing the Impact of AI in Leadership

As organizations continue to embrace AI-driven leadership practices, the potential for transformative impact is vast. By harnessing the power of AI, leaders can unlock new opportunities, drive innovation, and navigate complex challenges with confidence. From predictive analytics to autonomous decision-making systems, the possibilities are endless for those who dare to embrace the future of leadership.

Trending Industry Stats:

A study by Accenture found that AI adoption could lead to an economic boost of $14 trillion by 2035, driven by productivity gains and increased innovation.

The Global AI Survey conducted by McKinsey & Company revealed that 63% of executives believe that AI has the potential to significantly impact their businesses within the next five years.

Insights on Top Performers:

Apple Inc. utilizes AI technologies such as Siri and facial recognition in its products to enhance user experiences and drive customer satisfaction. With a focus on privacy and security, Apple demonstrates how AI can be leveraged responsibly to deliver value.

Walmart, one of the world's largest retailers, leverages AI for inventory management, demand forecasting, and supply chain optimization. By utilizing AI-driven insights, Walmart enhances operational efficiency and delivers superior customer service.

Ethical Considerations and Responsible Leadership

As AI continues to permeate every aspect of leadership, ethical considerations become increasingly paramount. Leaders must prioritize ethical decision-making, transparency, and accountability to ensure that AI technologies are deployed responsibly and uphold societal values.

Trending Industry Stats:

A survey by Deloitte found that 82% of executives believe that ethical risks associated with AI are a significant concern for their organizations.

The IEEE Global Initiative for Ethical Considerations in Artificial Intelligence and Autonomous Systems highlights the importance of ethical guidelines and standards in AI development and deployment.

Insights on Top Performers:

Google's parent company, Alphabet Inc., has established an AI Ethics Council to oversee the responsible development and deployment of AI technologies. By integrating ethical considerations into its AI initiatives, Alphabet demonstrates its commitment to responsible leadership.

Salesforce, a leading provider of customer relationship management (CRM) software, prioritizes ethical AI practices in its products and services. Through initiatives such as the Office of Ethical and Humane Use of Technology, Salesforce ensures that AI technologies are aligned with ethical principles and values.

The Role of Leadership Development in AI Adoption

Effective leadership development plays a pivotal role in enabling organizations to harness the full potential of AI. By investing in training, education, and skill development, leaders can equip themselves with the knowledge and capabilities needed to leverage AI technologies effectively.

Trending Industry Stats:

According to LinkedIn's 2021 Workplace Learning Report, 61% of learning and development professionals believe that leadership development is a top priority for organizations investing in employee training.

The World Economic Forum's Future of Jobs Report highlights the growing demand for AI-related skills, with roles such as AI specialists and data scientists projected to experience significant growth.

Insights on Top Performers:

IBM offers a range of leadership development programs focused on AI, such as the IBM Leadership Academy. Through these programs, IBM empowers leaders to drive AI adoption and innovation within their organizations.

General Electric (GE) has implemented AI training initiatives for its leadership teams to ensure that they are equipped with the skills and knowledge needed to navigate the digital age. By investing in leadership development, GE stays ahead of the curve in AI adoption and implementation.

FAQs: Leadership with AI

Q: How can AI benefit leadership decision-making?

AI empowers leaders to make faster, more informed decisions by analyzing data, identifying patterns, and forecasting outcomes with greater accuracy.

Q: What role does AI play in driving innovation and creativity within organizations?

AI automates routine tasks, freeing up time for strategic thinking and fostering a culture of innovation and creativity.

Q: How can AI support leadership development within organizations?

AI-driven learning platforms provide personalized coaching, feedback, and training opportunities, enabling leaders to develop their skills and capabilities effectively.

Q: What are some examples of AI-powered tools that can benefit leadership?

A: Examples include data analytics platforms, decision-making tools, virtual assistants, and personalized learning systems.

Q: What challenges do organizations face when integrating AI into leadership practices?

A: Challenges may include data privacy concerns, ethical considerations, and the need for employee training and upskilling.

Q: How can organizations ensure ethical and responsible use of AI in leadership decision-making?

A: By establishing clear guidelines, promoting transparency, and fostering a culture of ethical decision-making.

Conclusion

In conclusion, the future of leadership lies at the intersection of AI and human ingenuity. By embracing AI technologies and leveraging them effectively, leaders can unlock new opportunities, drive innovation, and navigate challenges with agility and foresight. However, success in the AI-driven era requires more than just technological prowess—it demands ethical leadership, responsible decision-making, and a commitment to continuous learning and development. As organizations embark on their AI journeys, they must prioritize leadership development and invest in the skills, knowledge, and capabilities needed to thrive in the digital age. With the right mindset, tools, and strategies, leaders can harness the transformative power of AI to shape a brighter future for themselves, their organizations, and society as a whole

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dankusner · 6 months ago

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Dallas’ Ex-CIO Zielinski Takes Executive Role With Gartner

William Zielinski, former Dallas CIO, announced Thursday that he’s moved into an executive partner role with Gartner, stated to be the world’s largest IT research and advisory company.

Zielinski takes more than three decades of experience in public-sector technology with him.

“I am excited to announce that I have begun a new position with Gartner Inc. as an executive partner working with U.S.-based state and local executives,” he wrote on LinkedIn. “After 34 years of government service at the federal and local levels, I am thrilled to leverage my experience and passion for public service in this new role.

Having been a Gartner client in my prior IT executive roles, I am grateful to be joining a phenomenal team of experienced executive partners who have helped IT executives around the world improve the results they deliver for their organizations.”

He told Industry Insider — Texas last year that he wasn’t quite ready to leave public service upon departing the federal government and chose Dallas, where he served from June 2020 to April of this year.

Zielinski’s career includes stints as assistant commissioner of the IT category for the General Services Administration and the executive lead for implementing the governmentwide Federal Information Technology Acquisition Reform Act, and he served as CIO of the Social Security Administration.

“I was thinking about end-of-career aspirations and goals. I didn’t want to leave government — I’m the child of public servants. I wanted to get back into operations where I was much closer to those who I’m trying to serve,” he said. “So where better to do that than in a city, and where better to do that than the ninth-largest city in the nation, right? There was some natural kind of alignment between what I would like to do as I close out my career and opportunities that made themselves available in the city of Dallas.”

Zielinski spoke passionately of Dallas’ IT operations and smart cities projects.

When the city suffered a highly visible data breach, Zielinski was confident his team could turn it around in the shortest time possible due to their incident response planning.

“The city employs a formal incident response plan, which defines the detailed steps and processes that must be followed to determine, classify, respond to and remediate an incident,” he reported afterward.

Among milestones, he previously told Industry Insider that a regional public safety radio system would top the list.

“We’ve implemented and launched a brand-new P25-compliant public safety radio system that is a regional deployment.

While we are the service provider — we, the city of Dallas, are the ones who are operating that with Motorola, who is our prime vendor — it is actually a partnership.

We are utilizing radio tower infrastructure from a multitude of different jurisdictions,” he said. “This system is a significant improvement in the technology that’s available, to not just our folks in the city, but to the entire region.”

This story originally appeared in Industry Insider — Texas, a sister publication to Government Technology.

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informative1-blogs · 6 months ago

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Transforming Industries with AI Automation Solutions

Automation solutions, driven by Artificial Intelligence (AI), are revolutionizing various industries by transforming how they operate. According to Gartner, Inc., by 2025, 75% of B2B sales organizations will replace traditional sales playbooks with AI-guided solutions. This transition is fueled by advancements in AI, deep learning, and robotics, marking the dawn of a new age of automation solutions.

The Rise of Automation Solutions

AI Business Automation

The recent developments in AI business automation have unlocked new opportunities for progress. Companies worldwide are increasingly moving from manual processes to advanced AI solutions, recognizing their long-term benefits. AI business automation includes tools that handle a wide range of tasks, from customer service chatbots to predictive analytics. These solutions allow businesses to automate routine tasks, freeing employees to focus on more strategic activities. For example, AI can analyze vast datasets to provide insights that were previously unattainable through manual methods.

Transforming Sales Training

Sales training is evolving beyond traditional methods to incorporate AI technology. Gartner's research highlights that modern sales training now includes critical thinking and data literacy—essential skills for today's sales professionals. AI tools can provide personalized training programs, monitor performance, and suggest improvements. With AI increasingly integrated into daily activities—from sensor lights to autonomous driving—sales playbooks must adapt to include AI in everyday business operations. This shift not only enhances efficiency but also helps sales teams stay competitive in an increasingly digital marketplace.

Addressing Key Challenges with Automation Solutions

Segmentation and Data Management

Managing data manually is a significant challenge, but AI makes it seamless. AI-powered tools automatically segment data based on demographics, customer preferences, and client status, offering real-time updates and greater accuracy. Traditional data management methods often lead to errors and inefficiencies. In contrast, AI-enabled tools ensure that customer interactions are tracked accurately and systems are updated promptly. For instance, an e-commerce platform can use AI to segment customers based on their browsing behavior and purchase history, enabling personalized marketing strategies.

Personalization

The demand for personalization extends to emails, notifications, and other customer interactions. AI business automation tools enable organizations to address customers by name, tailor content to their interests, and provide a more engaging experience. Personalization fosters deeper customer engagement and a sales-centric approach. AI can analyze customer data to understand preferences and behaviors, allowing businesses to create personalized marketing campaigns that resonate with their audience. This approach not only improves customer satisfaction but also increases conversion rates and loyalty.

Automated Workflows

AI-driven automated workflows streamline operational activities across industries. In both B2B and B2C sectors, automated workflows handle data management, approvals, order management, and customer queries efficiently. AI's self-learning capabilities ensure smooth and consistent operations. For instance, in manufacturing, AI can optimize production schedules and inventory management, reducing downtime and improving efficiency. Similarly, in customer service, AI-powered chatbots can handle routine inquiries, freeing up human agents to tackle more complex issues.

Forecasting and Decision-Making

AI excels at evaluating unknown situations, such as demand fluctuations and changing trends. By analyzing individual preferences and seasonal factors, AI helps businesses make informed decisions about production and inventory management. AI-enabled workflows route orders more effectively, meeting business needs faster and more cost-efficiently. For example, retailers can use AI to predict product demand based on historical data and current market trends, ensuring they stock the right products at the right time. This proactive approach reduces overstock and stockouts, leading to better inventory management and customer satisfaction.

Handling Mundane and Repetitive Tasks

Automated workflows are ideal for repetitive tasks that often lead to human errors. AI helps companies manage large-scale operations efficiently, ensuring competitiveness and reducing redundancy. Repetitive tasks, such as data entry and processing, are prone to errors and can be time-consuming. AI can automate these tasks, increasing accuracy and freeing up employees to focus on more value-added activities. For instance, AI can automate the process of sorting and categorizing emails, ensuring that important messages are prioritized and addressed promptly.

Risk Management

AI enhances risk management by ensuring data privacy and security. Automated business operations minimize human errors and legal challenges, safeguarding sensitive information. AI can monitor systems for potential threats, analyze security data, and respond to incidents in real time. This proactive approach to risk management helps businesses protect their assets and maintain compliance with regulatory requirements. Additionally, AI can help identify and mitigate financial risks, such as fraud detection and credit scoring, by analyzing large datasets for unusual patterns and anomalies.

Enhancing User Experience (UX)

AI transforms how customers interact with brands by understanding and anticipating their needs. AI enhances user experience and fosters better communication between businesses and their audience. AI-powered tools can analyze customer behavior and preferences, enabling businesses to provide personalized recommendations and support. For example, an online retailer can use AI to recommend products based on a customer's browsing history and previous purchases, creating a more engaging shopping experience. AI also powers virtual assistants and chatbots that provide instant support, improving customer satisfaction and loyalty.

Boosting Business Efficiency

Efficiency is crucial in today's competitive business landscape. AI business automation addresses manual challenges and ensures continuous, uninterrupted operations. AI-driven efficiency helps businesses stay ahead without increasing costs. For instance, AI can optimize supply chain management by predicting demand, reducing lead times, and minimizing inventory costs. In the healthcare industry, AI can streamline administrative tasks, such as patient scheduling and billing, allowing healthcare professionals to focus on patient care. By automating routine tasks, businesses can achieve higher productivity and operational efficiency, ultimately driving growth and profitability.

The COVID-19 pandemic accelerated the obsolescence of manual business operations, making way for AI, Machine Learning, and Deep Learning. AI business automation is driving significant changes in businesses and economies worldwide. As Gartner and other experts predict, AI's role in business management will continue to grow, becoming a permanent fixture in both B2B and B2C industries. By 2025, organizations of all sizes will adopt AI services to maintain their competitive edge. AI is not just an emerging trend; it is a permanent solution that will shape the future of business operations.

FAQs

1. What are automation solutions?

Automation solutions involve using AI and other technologies to automate routine business tasks, enhancing efficiency and accuracy. These solutions can be applied across various industries to streamline processes, reduce costs, and improve productivity.

2. How can AI improve personalization in marketing?

AI can analyze customer data to tailor content and interactions, creating a more personalized and engaging experience for each customer. By understanding customer preferences and behaviors, businesses can deliver targeted marketing campaigns that resonate with their audience, increasing conversion rates and customer loyalty.

3. What are the benefits of AI in risk management?

AI improves risk management by ensuring data privacy and security, reducing human errors, and minimizing legal challenges. AI-powered tools can monitor systems for potential threats, analyze security data, and respond to incidents in real-time, helping businesses protect their assets and maintain compliance with regulatory requirements.

Reference: https://addonez.com/maximize-efficiency-with-expert-automation-solutions/

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