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Sidestepping AI’s Pitfalls: The Unforeseen Implementation Risks

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The genie is out of the bottle, with AI poised to grant the wishes of every competitive enterprise with efficiency, profit, and growth. However, relying on the promises of nascent technology heedless of its potential pitfalls can undermine its eagerly anticipated benefits. Companies risk mismanaging massive amounts of data without defining and aligning tangible business goals with clear objectives. Rich Fennessy, CEO of Trace3, encourages businesses to develop robust data management strategies that support the successful integration of AI and other emerging technologies to avoid stagnation, increased cybersecurity threats, and missed financial opportunities.

IRVINE, Calif., July 8, 2024 /PRNewswire-PRWeb/ — It’s becoming less a matter of “if” or “when” companies will incorporate AI tools into their business model, but rather “how” they will integrate its advantages into their daily operations. According to research conducted by Exploding Topics, 77% of companies are currently using or exploring the applications of AI in their businesses, with 83% reporting that AI is a top priority in their future plans. Nine out of ten organizations believe AI offers a competitive advantage. (1) However, despite all the optimism surrounding its limitless possibilities, 70% to 80% of all AI projects fail. (2) Rich Fennessy, CEO of Trace3, advises, “To mitigate the financial risks associated with the high failure rate of AI projects, companies should adopt a practical and strategic approach. Focus on selecting the right use cases that align closely with business objectives and offer clear, measurable outcomes. Prioritize high-impact, feasible projects that can demonstrate quick wins, thereby building confidence and securing further investment.”

“Maintaining a competitive edge in today’s AI-driven landscape requires a purposeful approach,” emphasized Rich Fennessy, CEO of Trace3. “It’s about aligning technology with business strategy and ensuring AI readiness for success.”

Emerging technologies arrive in tandem with associated risks that are often overlooked. Misalignment with strategic goals can lead to poor ROI and low buy-in and shortcuts in technology infrastructure impede progress and increase costs. The demand for experts and workforce retraining slows adoption, while a lack of expertise among executives can impact decision-making and risk assessment. Treating emerging technology as incremental improvement rather than transformative can limit success. The lightning-fast pace of innovation can outpace risk assessment and regulation, leading to safety and security concerns. Large volumes of data create vulnerabilities that require data governance, secure infrastructure, and compliance measures. (3)

Essential Strategies for Successful Technology Integration
Fennessy offers the following solutions to successfully overcome the inherent risks when implementing emerging technology like AI:

1. Develop Robust Data Management Strategies for AI Integration: Data preparation is essential, as many enterprises struggle with data quality and availability issues. Establish strong data governance with clear policies for quality, security, and privacy. Use data profiling to identify inconsistencies and anomalies. Implement scalable architectures like data lakes or warehouses to store, manage, and organize diverse data types efficiently.
2. Align AI Projects With Business Objectives: Engage both business and technical stakeholders to identify specific AI use cases that align with business objectives and deliver measurable outcomes, using techniques like “art of the possible” workshops to uncover potential ideas. Conduct pilot projects to test and refine these use cases, focusing efforts on high-impact areas and being prepared to pivot if necessary.
3. Mitigate Financial Risks of AI Project Failures: Poor data quality and management are common reasons for AI project failures. Invest in reliable data assessment, cleansing, and validation. Establish strong data governance frameworks to maintain data integrity, security, and compliance. Choose the right platforms for AI deployment, such as cloud solutions offering advanced AI and machine learning tools, pre-built models, and infrastructure, significantly reducing initial setup costs and time.
4. Address Ethical Concerns in AI and Emerging Technologies: Communicate clearly on data usage and AI decision-making processes. Implement oversight mechanisms to prevent misuse and ensure compliance. Adhere to data protection regulations, employ anonymization techniques, and audit AI systems to identify and mitigate bias.
5. Balance Operational Disruptions with Innovation: AI should be implemented as an integral business component, requiring visionary leadership and a culture of testing assumptions to foster technical trust. While explainability is crucial in critical use cases, preparing for future adoption remains essential for evolving technologies.
6. Cybersecurity Measures for Emerging Technologies: Organizations must ensure transparency in data handling, aligning with the General Data Protection Regulation (GDPR), California Consumer Privacy Act (CCPA), and other privacy standards while enhancing anonymization and cybersecurity. Mitigating bias involves using diverse datasets, regular audits, and adopting bias detection tools for AI. Establishing ethical AI frameworks and ongoing employee education promotes responsible deployment aligned with organizational values.
7. Ensure Regulatory Compliance in Technology Implementations: Regular risk assessments identify tech vulnerabilities and monitor threats. Solid security systems like the NIST Cybersecurity Framework, ISO/IEC 27001, and CIS Controls ensure comprehensive protection with advanced endpoint security, network segmentation, encryption, and strong access controls. Implementing vulnerability management, incident response plans, and ongoing training to defend against cybersecurity threats are crucial for organizations using third-party services.

Trace3 transforms enterprises through collaborative, strategic consulting, adaptive technology, and convergent solutions that deliver visible and measurable results. Fennessy concludes, “Maintaining a competitive edge in today’s AI-driven competitive landscape requires a purposeful approach. It’s not simply about getting on board with the latest technology, it’s about bending it to align with your strategy and desired business outcomes, while ensuring your AI data readiness supports a roadmap that leads straight to success.”

About Trace3:
Today there is a great deal of noise in the technology industry around AI, but not much practical intelligence is offered. Trace3, based in Irvine, California, delivers over 20 years of expertise in delivering innovation in the form of emerging technology, providing unique technology solutions and consulting services to change this – and drive its implementation across enterprises. Their elite engineering and dynamic innovation provide convergent solutions that embrace emerging technology and drive measurable value. Trace3 embodies the spirit of a startup with the advantage of a scalable business. Trace3 believes that ALL Possibilities Live in AI. For more information, visit http://www.trace3.com.  

References:
1. Tprestianni. “131 AI Statistics and Trends for 2024.” National University, 1 Mar. 2024, nu.edu/blog/ai-statistics-trends/#:~:text=According%20to%20research%20completed%20by,priority%20in%20their%20business%20plans.
2. Rschmelzer. “Top Reasons Why AI Projects Fail.” Cognilytica, 26 Dec. 2023, cognilytica.com/top-10-reasons-why-ai-projects-fail/#:~:text=The%20Shocking%20Truth%3A%2070%2D80%25%20of%20AI%20Projects%20Fail!,-Despite%20the%20buzz&text=Not%20surprisingly%2C%20there%20are%20a,ways%20to%20navigate%20these%20challenges.
3. “Eight Overlooked Emerging Tech Risks and How to Mitigate Them.” ISACA, isaca.org/resources/news-and-trends/newsletters/atisaca/2024/volume-9/eight-overlooked-emerging-tech-risks-and-how-to-mitigate-them. Accessed 1 July 2024.

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In Turfan, Xinjiang, China’s first commercially operated microgrid has generated nearly 100 million kWh of electricity

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TURFAN, China, Nov. 15, 2024 /PRNewswire/ — On November 13, the Turfan New Energy City Microgrid Demonstration Project, China’s first commercially operated microgrid demonstration project, generated nearly 100 million kWh of electricity, equivalent to saving 29,000 tons of standard coal and reducing carbon dioxide emissions by 77,600 tons.

A microgrid refers to a small-scale power generation and distribution system organized by distributed power sources, power loads, distribution facilities, monitoring and protection devices, etc., which can realize flexible control and autonomous management. Since the end of 2013, the project had been the largest and most comprehensive solar energy utilization and building integration project in China up to that time, with 8.7 MW of photovoltaic power installed on the roofs of 223 residential buildings, generating an annual power capacity of about 10 million kWh.

To promote the physical operation of the project, the State Grid Turfan Power Supply Company invested more than 2 million yuan to cooperate in the construction of microgrid infrastructure, fully supporting the online operation of surplus new energy power generation, promoting the comprehensive utilization of renewable resources in urban buildings, and helping Turfan build a high-quality development demonstration area and a green and low-carbon pilot area.

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SOURCE State Grid Turfan Power Supply Company

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Innovations in Guiyang: Adhering to New Industrialization and Promoting High-End, Intelligent and Green Manufacturing

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GUIYANG, China, Nov. 15, 2024 /PRNewswire/ — A report by Huanqiu.com

The wave of new industrialization in Guiyang is driving the transformation and upgrading of the manufacturing industry in ways like never before. Guiyang is always strategically oriented toward “industrial structure optimization with a focus on industries”, and has made all efforts to develop “four major industrial bases”, highlighting its industrial economy as the “primary driving force” behind development. Especially relying on its policy edge in renewable energy, Guiyang has rapidly emerged as a national new-energy power battery and materials research, development and production center, injecting strong momentum into the city’s economy.

In October 2023, the CATL (Guizhou) New Energy Power and Energy Storage Battery Production Base, located in Gui’an New Area, Guizhou Province, was put into production. The first phase of the base boasts cutting-edge design standards, characterized by “lighthouse + zero carbon factory”. The high-standard facility employs advanced, high-speed, highly automated, and flexible production lines. It is designed to have an annual production capacity of 30 GWh. After the base achieves the designed production capacity, its annual output value is expected to reach 15 billion yuan. According to statistics, the base realized an industrial output value of 618 million yuan in the first half of 2024, and the year’s industrial output value is expected at about 2 billion yuan.

The Chery (Guizhou) industrial base has also yielded unusually brilliant results in the field of new energy vehicles (NEVs), where Chery Automobile’s self-developed “CHEVOO” new-generation light truck KL71 project is undergoing four-pillar car road tests. The advanced pressing, welding, painting and assembly lines, as well as the R&D lab and the all-electric truck production line, together constitute this “digital intelligent” NEV factory. Moreover, the Chery (Guizhou) industrial base has built, extended and strengthened its vehicle manufacturing industry chain so as to master key parts supply chains and reduce development costs.

The Gui’an FinDreams battery project, as an important move of BYD in Guiyang, is also showing its strength in power batteries for NEVs. FinDreams Battery Co., Ltd. at Longshan Industrial Park in Gui’an New Area has four automatic production lines that are operating at high speeds in the workshop, which produce “blade batteries” which are well-known both in and out of the industry. According to reports, 300 battery packs and 40,000 cells can be produced per day.

Guiyang’s “four bases” – a new energy vehicles and battery materials production base, a resource deep-processing base, a computing power assurance base, and an industrial backup base, contribute greatly to the development of NEV and battery materials industry, electronic information manufacturing industry, and advanced equipment manufacturing industry, etc. Data show that in the first three quarters, the added value of Guiyang’s industrial enterprises above designated size grew by 11%, and the contribution of industrial economy to economic growth reached 39.4%.

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Premialab appointed by Lombard Odier Investment Managers to scale Quantitative Investment Strategies

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Premialab’s technology chosen to enhance QIS scaling, operational efficiency, and risk management.

PARIS, Nov. 15, 2024 /PRNewswire/ — Lombard Odier Investment Managers (LOIM), the institutional asset management business of the Lombard Odier Group, has integrated Premialab‘s industry-leading technology to support the management of their soon-to-be-launched DOM Global Macro strategy. This partnership underscores LOIM’s commitment to onboard innovative strategies in an evolving market landscape.

“Our decision to partner with Premialab is driven by their comprehensive risk management and regulatory compliance expertise,” said Didier Anthamatten, Portfolio Manager at LOIM. “With a strong track record in alternative investments, LOIM remains focused on delivering innovative investment solutions and high-quality returns for our clients. Premialab’s advanced data capabilities are essential in helping us maintain our rigorous standards and provide robust, risk-adjusted performance. Additionally, their platform perfectly matches the DOM Global Macro strategy’s needs, enhancing our risk monitoring capabilities and streamlining portfolio management.”

The DOM Global Macro strategy expects to leverage Premialab’s unique dataset. The full lookthrough across all DOM’s proprietary systematic strategies allows granular risk decomposition and scenario-based analysis at the entire portfolio level. This should help monitoring exposures’ attractiveness, from both time-series and cross-sectional perspectives, and optimizing asset allocation.

Neil Richards, Head of EMEA Business Development at Premialab, said the collaboration with LOIM is a significant addition to Premialab’s growing business in Switzerland and within the wider European markets.

“Institutions such as LOIM, which oversees a substantial portfolio across various asset classes, need continuous monitoring and adjustment to keep their investments on track,” he explained. “Premialab provides the tools for benchmarking and stress testing their systematic investments, ensuring that LOIM’s mandates are effectively managed in terms of cost, risk, and value.”

Premialab CEO Adrien Géliot highlighted that the QIS sector is experiencing rapid growth, driven by institutional investors seeking liquid, transparent, and cost-efficient investment strategies. “Premialab sits at the centre of the QIS landscape, uniquely positioned to aggregate and make sense of the vast and growing universe of data,” he stated. “We are thrilled to be partnering with LOIM to deliver our unique data and risk monitoring capabilities to one of the top global investment firms.”

Premialab’s multi-asset, multi-region platform handles 10 million data points daily. It analyzes over 5,000 investible systematic strategies, with client assets under management totalling approximately USD $20 trillion. Combining the Premialab platform with Premialab Pure Factors®, it provides comprehensive cross-asset quantitative strategy selection and thorough due diligence on strategies available worldwide. Additionally, the platform enhances risk management and reporting capabilities, including expedited and detailed regulatory reporting.

With its unique combination of systematic strategies and discretionary trading, the DOM Global Macro strategy clearly benefits from Premialab’s state-of-the art data analysis capabilities and computational efficiency. The Portfolio and Risk Managers can thus use a shared dataset for risk analysis and performance decomposition, enhancing the portfolio’s robustness and operational efficiency.

About Premialab
Premialab is the leading independent platform that collaborates with leading investment banks and institutional investors globally, providing data, analytics, and risk solutions for systematic, factor, and multi-asset strategies. With offices in London, Paris, New York, Hong Kong, Dubai and Sydney, the company has forged strong partnerships with the top 18 investment banks, asset managers, pension funds, sovereign wealth funds and insurance companies globally.

About Lombard Odier Investment Managers (LOIM)
Lombard Odier Investment Managers (LOIM) is the institutional asset management business of the Lombard Odier Group, wholly owned and funded by its partners since its establishment in 1796.

We provide a range of investment solutions to a diverse group of long-term oriented clients. Our heritage, and our combination of the best of conservatism and innovation, keeps us well positioned to create lasting value for our clients. Our investment capabilities span fixed income, convertible bonds, equities, multi-asset, and alternatives. Sustainability is central to our investment philosophy; we believe it is the founding principle of long-term economic and investment outcomes and will drive returns over the long term.

With over 200 investment professionals, we are a global business with a network of 13 offices across Europe, Asia and North America and have assets under management of CHF 64 billion (as at 31 September 2024).

View original content:https://www.prnewswire.com/de/pressemitteilungen/premialab-appointed-by-lombard-odier-investment-managers-to-scale-quantitative-investment-strategies-302306411.html

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