Info@NationalCyberSecurity
Info@NationalCyberSecurity

Industry leaders on AI, cybersecurity, and tech trends in 2024 | #hacking | #cybersecurity | #infosec | #comptia | #pentest | #ransomware


In the ever evolving tech landscape, the transformative potential of AI extends beyond innovation to cybersecurity. As we enter 2024, industry leaders highlight that AI-powered cybersecurity plays a crucial role in threat detection and response, userization and AI revolutionizes user experiences and efficiency across applications, XaaS accelerates the implementation of digital services and Generative AI emerges as a pivotal component within enterprise software solutions. The collective insights from these tech titans provide a comprehensive view of the challenges and opportunities that lie ahead.

 

CrowdStrike

Elia Zaitsev, CTO, CrowdStrike
CISOs and CIOs turn to platforms to drive the best security and IT outcomes.
With CISOs and CIOs being tasked to do more with less, in 2024 we will see an industry-wide shift as organizations turn to platforms, rather than legacy point solutions, that break down operational silos and reduce complexity and cost. The increased collaboration between CISOs and CIOs is driving the need for a platform that can be the solution to both of their problems – an AI-native platform that stops breaches and provides a cost-effective single point of control for CIOs.

AI Blind Spots Open the Door to New Corporate Risks. In 2024, CrowdStrike expects that threat actors will shift their attention to AI systems as the newest threat vector to target organizations, through vulnerabilities in sanctioned AI deployments and blind spots from employees’ unsanctioned use of AI tools.

After a year of explosive growth in AI use cases and adoption, security teams are still in the early stages of understanding the threat models around their AI deployments and tracking unsanctioned AI tools that have been introduced to their environments by employees. These blind spots and new technologies open the door to threat actors eager to infiltrate corporate networks or access sensitive data.

Critically, as employees use AI tools without oversight from their security team, companies will be forced to grapple with new data protection risks. Corporate data that is inputted into AI tools isn’t just at risk of threat actors targeting vulnerabilities in these tools to extract data, the data is also at risk of being leaked or shared with unauthorized parties as part of the system’s training protocol.

2024 will be the year when organizations will need to look internally to understand where AI has already been introduced into their organizations (through official and unofficial channels), assess their risk posture, and be strategic in creating guidelines to ensure secure and auditable usage that minimizes company risk and spend but maximizes value.

In addition, adversaries will see cloud-based AI resources as a lucrative opportunity. While many believe that AI will be a top trend in enterprise investment over the next few years, a recent study found that 47% of cybersecurity professionals admit to having minimal or no technical knowledge of AI. On top of that, AI presents new security challenges, as AI systems require access to large datasets often stored in the cloud. Securing this data and ensuring that AI models running in the cloud are not exploited for malicious purposes will be a growing concern, and in 2024, a comprehensive Cloud Native Application Protection Platform (CNAPP) will be more important than ever to fend off opportunistic adversaries.

 

EQUINIX INDIA

Manoj Paul, Managing Director, Equinix India

As we approach 2024, the global shift toward a digital-first future intensifies, with digital infrastructure emerging as a cornerstone for businesses to gain a competitive edge in the ever-expanding digital economy. This evolution brings forth several innovations and digital trends that promise to reshape the landscape of data centers and digital services, fostering a sustainable and interconnected environment.

The delicate balance between maximizing AI value and safeguarding sensitive data prompts the exploration of private AI—an environment exclusively tailored for organizational use. This innovative approach enables enterprises to harmonize AI strategy execution while retaining control over valuable data, marking a significant advancement in the digital realm. The growing enterprise adoption of cloud computing and the focus on edge computing and AI to process and analyze data closer to the source will also require increasingly flexible and hybrid approaches to digital infrastructure.

With the AI revolution, Everything as a Service (XaaS) accelerates the implementation of digital services. This on-demand model allows enterprises to seamlessly integrate new digital capabilities at software speed, scaling up or down as per business needs. Equinix champions XaaS through Platform Equinix®, empowering users to interconnect and adopt emerging technologies for a competitive edge.

Another trend revolutionizing data centers is liquid cooling, a response to the escalating adoption of AI and high-performance computing (HPC) applications. Liquid cooling surpasses air efficiency, enabling higher rack density and improved cooling performance. Equinix will expand support for advanced liquid cooling technologies –like direct-to-chip- to more than 100 of our International Business Exchange® (IBX®) data centers in more than 45 metros, including Mumbai and Chennai.

Cloud-Adjacent Storage emerges as a solution to evolving data storage challenges. The expansion of public cloud, the accelerated adoption of AI and the need to derive meaningful insights from data all put pressure on organizations to optimize the placement, control and security of their most valuable asset – data. At Equinix, we offer cloud-adjacent storage services with our partners, including NetApp, Pure Storage, and more, to enable customers to maintain control of their data, optimize costs, and provide high performance for their most demanding workloads.

 

Whatfix

Vara Kumar Namburu, Co-Founder & CTO, Whatfix

AI has been around for a while. The advent of Gen-AI brought it to the fore, presenting the potential to carve the next decade of innovation for the world. Gartner predicts that 80% of enterprises will have deployed generative AI-enabled applications by 2026. Today we are only scratching the surface by providing abilities to read documents, provide summaries etc. In its full bloom, gen-AI will enhance productivity in every part of the business. For all of this to become a reality, the Quality of generative AI has to get to production-grade, costs have to come down, and performance has to improve.

With the employee experience (EX) being added to the CIO’s charter alongside CX, the HR tech awaits a revolution. DX tools like digital adoption platforms (DAPs), with intuitive guidance in the flow of work, will drive the change in how employees engage with digital tools. The amalgamation of AI with the innovation concept of userization —making technology user-savvy, and unburdening the employees to become tech-savvy— is key in aligning with the broader shift of technology from cohorts to unique-user needs.

All the innovation will still need analytics to elevate the product and EX as well as CX by deciphering unique user behavior and feedback, providing strategic insights for informed decision-making. Embracing these tech shifts necessitates addressing the human side, emphasizing upskilling to navigate the digital age. Security-wise, 2024 demands vigilant measures against evolving cyber threats, with AI-driven detection and stringent data privacy practices at the forefront.

At Whatfix the union of userization and AI revolutionizes user experiences and efficiency across applications. Our human-in-the-middle approach ensures that AI complements and does not compete with humans offering businesses and IT leaders greater control. In 2024, AI and the workforce will continue to strengthen their dynamic partnership exemplifying the possibilities of responsible and inclusive technological integration, charting a future where humans and intelligent machines flourish side by side.

 

MediBuddy

Enbasekar D, Co-founder & CTO, MediBuddy

While 2023 saw the emergence of LLM in a big way, in 2024, we can expect Advanced AI, generative AI, and LLMs to become more prevalent in use across the tech industry. We can expect multiple startups emerging in the space to reimagine user experiences or enable other businesses to adopt LLMs or build custom, fine-tuned models or even localization and multilingual models.

Advanced AI and machine learning models are also poised to transform healthcare delivery through predictive, preventative, and personalised care applications. The adoption of such technologies will be gaining more acceptance among clinical experts and doctors as essential assistive tools in their practice. This, in combination with ABHA health ID and predictive monitoring and preventive diagnostics, will help the user track their health proactively.

 

ASCENDION

Mijitha Muralidharan, Associate Director, Engineering Services, Ascendion

 In 2024, there would be a strategic shift in the tech landscape, with Generative AI emerging as a pivotal component within enterprise software solutions, which will collaboratively shape digital products and services, marking a significant evolution in software development methodologies.

  • The rise of the Industrial Metaverse represents a paradigm shift beyond conventional digital twinning. It is poised to transcend the confines of replicating machinery or manufacturing plants, evolving into a robust 3D platform. This platform will extend its utility across entire organizations, value chains, and product life cycles, serving as a comprehensive digital reflection of an organization within its operational context.
  • Intelligent Automation is set to redefine the automation landscape in 2024. By amalgamating task and rules-based automation of RPA with cutting-edge AI technologies such as machine learning, natural language processing (NLP), and computer vision, it enables the seamless automation of intricate, decision-based business processes. This trend will facilitate holistic automation solutions through user-friendly low-code or no-code applications.
  • As we look ahead, Sustainable Technology will rightfully take center stage, with organizations increasingly investing in technologies that foster environmental, social, and governance (ESG) outcomes. This strategic emphasis reflects a commitment to responsible business practices and aligns with the evolving expectations of stakeholders.

Emerging technologies are set to transform business strategies, driving a new era of agility, efficiency, and innovation. Companies will streamline operations, leverage data for decision-making, and create personalized customer experiences. The integration of AI, metaverse platforms, intelligent automation, and sustainable tech will redefine business models, emphasizing adaptability and sustainability. This comprehensive approach enhances competitiveness in a dynamic global landscape, with a central focus on elevating consumer experiences through Generative AI, advanced data, and analytics, optimizing efficiency, minimizing errors, and enabling strategic leverage through refined tools such as predictive analytics and Large Language Models (LLMs).

Advanced algorithms and predictive analytics empower organizations to proactively anticipate and address threats, fortifying security protocols and enhancing defense posture against emerging risks. AI-powered cybersecurity is instrumental in Threat Detection and Response, providing a robust defense against AI threats. Machine learning algorithms analyze vast datasets in real time, identifying anomalies and security breaches. AI-driven threat detection systems excel in recognizing behavioral patterns often missed by human analysts. This proactive cybersecurity approach significantly reduces response times, mitigating the impact of AI-driven attacks. The transformative potential extends to enhancing enterprise posture through automated configuration hardening, addressing micro-segmentation challenges, refining least privilege access, improving reporting, and more.

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