Latest news with #Workhelix
Mint
26-04-2025
- Business
- Mint
Companies are struggling to drive a return on AI. It doesn't have to be that way.
AI adoption among companies is stunningly high, but most of them are struggling to put it to good use. They intuit that AI is essential to their future. Yet intuition alone won't unlock the promise of AI, and it isn't clear to them which key will do the trick. As of last year, 78% of companies said they used artificial intelligence in at least one function, up from 55% in 2023, according to global management consulting firm McKinsey's State of AI survey, released in March. From these efforts, companies claimed to typically find cost savings of less than 10% and revenue increases of less than 5%. While the measurable financial return is limited, business is nonetheless all-in on AI, according to the 2025 AI Index report released in April by the Stanford Institute for Human-Centered Artificial Intelligence. Last year, private generative AI investment alone hit $33.9 billion globally, up 18.7% from 2023. The numbers reflect a 'productivity paradox," in which massive improvements in AI capabilities haven't led to a corresponding surge in national-level productivity, according to Stanford University economist and professor Erik Brynjolfsson, who worked on the AI Index. While some specific projects have been enormously productive, 'many companies are disappointed with their AI projects." For companies to get the most out of their AI efforts, Brynjolfsson advocates for a task-based analysis, in which a company is broken down into fine-grained tasks or 'atomic units of work" that are evaluated for potential AI assistance. As AI is applied, the results are measured against key performance indicators, or KPIs. He co-founded a startup, Workhelix, that applies those principles. Companies should take care to target an outcome first, and then find the model that helps them achieve it, says Scott Hallworth, chief data and analytics officer and head of digital solutions at HP. A separate report from McKinsey issued in January helps explain why AI adoption is racing ahead of associated productivity gains, according to Lareina Yee, senior partner and director at the McKinsey Global Institute. Only 1% of U.S. companies that have invested in AI report that they have scaled their investment, while 43% report that they are still in the pilot stage. 'One cannot expect significant productivity gains at the pilot level or even at the company unit level. Significant productivity improvements require achieving scale," she said. The critical question then, is how companies can best scale their AI efforts. Ryan Teeples, chief technology officer of 1-800Accountant, agrees that 'breaking work into AI-enabled tasks and aligning them to KPIs not only drives measurable ROI, it also creates a better customer experience by surfacing critical information faster than a human ever could." The privately held company based in New York provides tax, booking and payroll services to 50,000 active clients, with a focus on small businesses. The company isn't a Workhelix customer. Additionally, he says, companies should look beyond individualized AI usage, in which employees use GenAI chatbots or AI-equipped productivity tools to enhance their work. 'True enterprise adoption…involves orchestration and scaling across the organization. Very few organizations have truly reached this level, and even those are only scratching the surface," he said. The use of AI at 1-800Accountant begins with an assessment of whether the technology improves the client experience. If the AI provides customers with answers that are as good, better or faster than a human, it's a good use case, according to Teeples. In the past, the company scheduled hourlong appointments with advisers who answered simple client questions, such as the status of their tax return. Now, the company uses an AI agent connected to curated data sources to address 65% of customer inquiries, with 30% arranging a call with a human. (The remaining 5% drop out of the inquiry process for various reasons.) The company uses Salesforce's Agentforce to handle customer inquiries and its Einstein platform for orchestration across 1-800Accountant's back end. Teeples said the company is saving money on the cost of human advisers. 'The ROI in this case was abundantly clear," he said. Orchestrating AI across the enterprise requires the right infrastructure, especially when it comes to data, according to Gabrielle Tao, senior vice president for data cloud at Salesforce. It is important, she said, to harmonize data, for example, by creating a consistent way to refer to business concepts such as 'orders" and 'transactions," regardless of the underlying data source. AI deployments should target tasks that are both frequent and generalizable, according to Walter Sun, global head of artificial intelligence at SAP. Infrequent, highly specific tasks such as a marketing campaign for a single event might benefit from AI, but applying AI to regularly occurring tasks will achieve a more consistent ROI, he said. Historically, it has taken years for the world to figure out what to do with revolutionary general-purpose technologies including the steam engine and electricity, according to Brynjolfsson. It isn't unusual for general-purpose models to follow a 'J-curve," in which there's a dip in initial productivity, as businesses figure things out, followed by a ramp-up in productivity. He says companies are beginning to turn the corner of the AI J-curve. The transformation may occur faster than in the past, because businesses—under no small amount of pressure from investors—are working to quickly justify the massive amount of capital pouring into AI. Write to Steven Rosenbush at
Yahoo
26-01-2025
- Business
- Yahoo
Palladyne AI Corp. (PDYN): Innovating Robotics with Autonomous AI Software
We recently published a list of . In this article, we are going to take a look at where Palladyne AI Corp. (NASDAQ:PDYN) stands against other top AI news updates you should not miss. Leading companies across diverse industries, including electronics, IT infrastructure, surveillance, renewable energy, robotics, and cybersecurity, are heavily investing in AI and machine learning to leverage the technology for widescale innovation. In turn, companies are able to reduce operational costs, tackle workforce challenges, and transform client experiences. For instance, in the IT infrastructure space, AI spending is expected to jump to $509.1 billion in 2027 from $175.9 billion in 2023, according to the IDC. The spending on AI platforms is expected to rise as they become increasingly important for business's digital operations. 'Harnessing machine learning can be transformational, but for it to be successful, enterprises need leadership from the top. This means understanding that when machine learning changes one part of the business — the product mix, for example — then other parts must also change. This can include everything from marketing and production to supply chain, and even hiring and incentive systems,' said Erik Brynjolfsson, co-founder of Workhelix. Elsewhere, PwC global chairman, Mohamed Kande, during his speech at the World Economic Forum in Davos urged people to not be afraid of AI in the workplace but embrace it as a digital colleague. 'People fear what they don't understand, so exposing them to the technology, putting in their hands makes a big difference,' Kande said about AI, adding that doing so allows employees to view AI as a 'digital colleague…You don't fear your colleagues, you partner with them…So we are actually asking people to partner with the technology.' For this article, we selected AI stocks by reviewing news articles, stock analysis, and press releases. We listed the stocks in ascending order of their hedge fund sentiment taken from Insider Monkey's database of 900 hedge funds. Why are we interested in the stocks that hedge funds pile into? The reason is simple: our research has shown that we can outperform the market by imitating the top stock picks of the best hedge funds. Our quarterly newsletter's strategy selects 14 small-cap and large-cap stocks every quarter and has returned 275% since May 2014, beating its benchmark by 150 percentage points (). Photo by NeONBRAND on Unsplash Palladyne AI Corp. (NASDAQ:PDYN), a robotics developer, offers an advanced AI and ML software platform transforming the capabilities of robots in terms of observation, learning, reasoning, and acting with unprecedented agility akin to human intelligence with minimal data sets, lower power requirements, and reduced training time. The AI software can equip most commercial robots with real-time environmental awareness to facilitate rapid adaptability to task variances without reprogramming through constant cloud connectivity, fostering high levels of autonomy and safety even in remote settings. On January 15th, Palladyne AI Corp. (NASDAQ:PDYN) and Red Cat Holdings (NASDAQ:RCAT) revealed that it completed the first successful flight involving Teal drones powered by Palladyne Pilot AI software, which autonomously coordinate to identify, prioritize, and track ground objects. The test demonstrated that Palladyne Pilot AI software enables multiple drones to autonomously collaborate and exchange sensor information seamlessly. 'The successful integration of Palladyne Pilot AI software into Teal drones to enable multi-drone autonomous collaboration is an important milestone in the partnership we announced with Red Cat last summer. We believe the force multiplier effect resulting from the autonomous collaboration capability of multiple drones will provide a substantial tactical advantage to the warfighter in the field,' said Matt Vogt, Chief Revenue Officer of Palladyne AI Corp. Overall, PDYN ranks 10th on our list of top AI news updates you should not miss. While we acknowledge the potential of PDYN as an investment, our conviction lies in the belief that AI stocks hold greater promise for delivering higher returns and doing so within a shorter time frame. If you are looking for an AI stock that is more promising than PDYN but that trades at less than 5 times its earnings, check out our report about the cheapest AI stock. READ NEXT: 20 Best AI Stocks To Buy Now and Complete List of 59 AI Companies Under $2 Billion in Market Cap Disclosure: None. This article is originally published at Insider Monkey. Sign in to access your portfolio
