The Role of CTOs in Integrating the Environmental, Social, and Governance Journey

There has always been a growing concern and realization of the need for environmental, social, and governance (ESG) factors as a critical component for successful business development across all sectors. From customers to stakeholders, regulators have been insisting companies consider the environmental impact and contribute their share of corporate social responsibility (CSR) programs to developing a greener society.

Consequently, with the rising competition, ESG factors have arisen as crucial considerations for IT organizations across the globe.

Therefore, to ignite that constant innovation and sustainability consciousness in a business, the Chief Technology Officer (CTO) must come forward to develop a strategic company by uniquely positioning the leverage of numerous technologies that eventually help the company stand out from its competitors.

Today’s exclusive AI Tech Park article aims to highlight the role of the CTO in the ESG journey and how implementing ESG will transform your IT organization.

The Relationship Between ESG and the CTO

The CTOs are the driving force behind the ESG initiative in an IT organization; however, the contribution of employees is equally vital to getting on board for a dignified project. The employees and C-suites need to understand the company’s vision and guide the CTO and IT employees to positively adopt the new ESG practices and prototype sustainability goals that will benefit the overall business. Let’s focus on some of the steps the CTOs can take to adopt their achievable sustainability goals:

Reputational Risk

The failure to integrate the ESG program into the business model can lead to reputational damage and legal risks for the IT firm. CTOs can clearly define their ESG agenda with the help of a supportive ESG team. Further, CTOs need to ensure that the investors are well aware of the required ESG information to let them participate in strategizing ESG goals rather than depending on third-party agencies.

As we move into a digitized business landscape, the incorporation of ESG has become an essential component of profitable business. The technologies implemented can be leveraged as a form of an ESG enhancement strategy with data and insights. CTOs and IT professionals also need to address ESG issues and integrate a modern approach that aligns security practices with business objectives.

To Know More, Read Full Article @ https://ai-techpark.com/the-role-of-ctos-in-esg/

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AITech Interview with Chris Conant, Chief Executive Officer at Zennify

Chris, could you start by introducing yourself and your role at Zennify and sharing a little about your background in the finance and technology sectors?

I joined Zennify in April 2023 as Chief Executive Officer. I’m a customer success and IT services veteran with over 15 years of experience in the Salesforce ecosystem and 30 years in technology.

Most recently, I was the Senior Vice President of Customer Success at Salesforce. I led the North American Success team responsible for ensuring the retention and growth of the $15B customer base. Before that, I was the COO of Model Metrics (acquired by Salesforce in 2011) and was a board advisor to Silverline and 7Summits, services firms within the Salesforce ecosystem. I was privileged to advise them on scaling and company growth.

We have a fantastic opportunity at Zennify to push boundaries and change the way consulting is done, using AI and tools to accelerate implementations and customer time to value. We strive to be the top boutique Salesforce and nCino consultancy for financial services firms. I’m proud to be here at Zennify and to continue upholding our reputation as one of the go-to partners for financial institutions that want to see accelerated outcomes.

Why financial institutions should ban AI at their own risk:

Chris, you’ve raised the idea that financial institutions should not ban AI at their own risk. Could you elaborate on why you believe AI is crucial for the financial sector’s future and what potential risks they face by not embracing it?

AI has and will continue to impact the breadth, depth, and quality of products and services offered by financial institutions. There are multiple use cases for AI – and a lot of them focus on increased efficiencies. For example, teams can use AI to better predict and assess loan risks, improve fraud detection, provide better and faster customer support through smarter personalization, and analyze data in unstructured ways – all while reducing costs. These are use cases that would have typically taken more time and have more room for errors. Understanding and implementing AI thoughtfully leads to sustainable business growth and staying ahead of your competitors.

To Know More, Read Full Interview @ https://ai-techpark.com/aitech-interview-with-chris-conant-ceo-at-zennify/

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Building a Fortified Wall: Effective Third-Party Risk Management Against Cyber Threats

In today’s interconnected business environment, companies regularly rely on third parties for critical business functions like supply chain, IT services, and more. While these relationships can provide efficiency and expertise, they also introduce new cybersecurity risks that must be managed. More than 53% of businesses worldwide have suffered at least one cyber attack in the past 12 months and one in five firms attacked said it was enough to threaten the viability of the business. Recent high-profile breaches like the SolarWinds attack have highlighted the dangers of supply chain compromises. Implementing a comprehensive third party risk management program is essential for security. In this post, we’ll explore key strategies and best practices organizations can use to defend against cyber threats from third party relationships.

Limit Access and Segment Third Parties

Once a third party relationship is established, limit their access to only what is required for their role. Segment them into their own virtual network or cloud environment isolated from your core infrastructure. Implement the principle of least privilege access for their credentials. Disable unnecessary ports, protocols, and services. Lock down pathways between your network and the third party. The goal is to reduce their potential impact and restrict lateral movement if compromised.

Continuously Monitor for Threats

Monitor third party networks vigilantly for signs of compromise. Deploy tools like intrusion detection systems that generate alerts for anomalous behavior. Monitor for unusual data transfers, unauthorized changes, malware, and other IOCs. Conduct vulnerability scans and penetration testing against your third parties’ environments. Audit their logs and security events for issues impacting your security posture. The goal is early detection that can limit damage from a third party breach.

Practice Incident Response Plans

Even rigorous security can still experience incidents. Develop plans for quickly responding to a breach impacting a third party. Define escalation protocols and response team roles. Maintain contacts for your third parties’ security staff. Institute plans for containment, eradication, and recovery activities to limit the impact on your organization. Practice responding to mock third party breach scenarios to smooth out the process. Effective incident response can significantly reduce the damage from real world attacks.

Foster Strong Relationships with Third Parties

While security requirements and controls are critical, also focus on building strong relationships with your vendors, suppliers, and partners. Collaborate to improve security on both sides. Offer guidance and training to enhance their practices and controls. Recognize those who exceed expectations. Build rapport at the executive level so security is taken seriously. Cybersecurity does not have to be adversarial – work together to protect against shared threats.

Third party risk management is essential in modern interconnected business ecosystems. Businesses can no longer rely solely on their own security – all external connections must be assessed and managed.
To Know More, Read Full Article @ https://ai-techpark.com/third-party-risk-management-strategies-against-cyber-threats/

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Buying Advice to Tackle AI Trust, Risk, and Security Management

In this technologically dominated era, the integration of artificial intelligence (AI) has become a trend in numerous industries across the globe. With this development of technology, AI brings potential risks like malicious attacks, data leakage, and tampering.

Thus, companies are going beyond traditional security measures and developing technology to secure AI applications and services and ensure they are ethical and secure. This revolutionary discipline and framework is known as AI Trust, Risk, and Security Management (AI TRiSM), which makes AI models reliable, trustworthy, private, and secure.

In this article, we will explore how chief information security officers (CISOs) can strategize an AI-TRiSM environment in the workplace.

Five Steps on How C-suite Can Promote Trustworthy AI in Their Organization 

The emergence of new technologies is likely to drive more potential risks; however, with the help of these five essential steps, CISOs and their teams can promote AI TRiSM solutions:

Defining AI Trust Across Different Departments

At its core, AI trust is the confidence that employees and other stakeholders have in a company that governs its digital assets. AI trust is driven by data accessibility, transparency, reliability, security, privacy, control, ethics, and responsibility. A CISO’s role is to educate employees on the concept of AI trust and how it is established inside a company, which differs depending on the industry and stakeholders. 

Develop an AI trust framework that helps achieve your organization’s strategic goals, such as improving customer connections, maximizing operational excellence, and empowering business processes that are essential to your value proposition. Once built, implement methods for measuring and improving your AI trust performance over time.

Ensure a Collaborative Leadership Mindset

As IT organizations rely on technology for back-office operations and customer-facing applications, IT leaders face the challenge of balancing business and technical risks, potentially leading to prioritizing one over the other.

CISOs and IT experts should evaluate the data risks and vulnerabilities that may exist in various business processes, such as finance, procurement, employee benefits, marketing, and other operations. For example, marketing and cybersecurity professionals might collaborate to determine what consumer data can be safely extracted, how it can be safeguarded, and how to communicate with customers accordingly.

As a CISO, you can adopt a federated model of accountability for AI trust that unites the C-suite around the common objective of seamless operation without hampering customers’ and organizations’ data. 

In conclusion, as businesses grapple with growing datasets and complicated regulatory environments, AI emerges as a powerful tool for overcoming these issues, ensuring efficiency and dependability in risk management and compliance. AI Trust, Risk, and Security Management (AI TRiSM) may assist businesses in protecting their AI applications and services from possible threats while ensuring they are utilized responsibly and compliantly.
To Know More, Read Full Article @ https://ai-techpark.com/tackling-ai-trism-in-ai-models/

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Revolutionizing BFSI with RPA and AI: A Solution-Based Approach

In today’s rapidly evolving business landscape, the Banking, Financial Services, and Insurance (BFSI) sector is at the forefront of digital transformation. To succeed in this dynamic environment, industry leaders, executives, and decision-makers must not only recognize the challenges but also harness the opportunities presented by technology. This article is a comprehensive exploration of how Robotic Process Automation (RPA) and Artificial Intelligence (AI) provide strategic solutions to address these challenges, foster innovation, and drive growth within the BFSI sector.

Before delving into their applications, let’s establish a clear understanding of RPA and AI. RPA utilizes software robots to automate repetitive tasks, while AI leverages machine learning and data analytics to replicate human intelligence. In BFSI, these technologies have the potential to reshape the way business is conducted.

Navigating Contemporary Challenges in BFSI

Before embarking on the journey of RPA and AI implementation, it’s crucial to acknowledge the pre-implementation challenges. Data security and regulatory compliance are critical in the financial services industry. Protecting sensitive customer data while adhering to strict industry regulations presents a complex puzzle. Furthermore, upskilling the workforce to adapt to these transformative technologies is a challenge that cannot be underestimated by CFOs, COOs, and industry professionals.

Potential of RPA and AI in BFSI:

RPA holds the power to streamline BFSI operations by automating laborious tasks such as data entry, transaction processing, and report generation. This not only reduces errors but also significantly improves operational efficiency. In parallel, AI ushers in a new era of data-driven decision-making within the sector. AI can predict market trends, detect fraudulent activities in real-time, and offer highly personalized product recommendations to customers. These capabilities lead to better customer experiences and more informed strategic decisions.

Solutions for Post-Implementation Challenges:

BFSI is an industry where every decision counts, embracing technology has become synonymous with staying competitive and relevant. As seasoned COOs, CFOs, banking professionals, and industry leaders, it is important to understand that the transformative power of Robotic Process Automation (RPA) and Artificial Intelligence (AI) can’t be ignored. While the potential of RPA and AI in BFSI is clear, the path to realizing these benefits can be laden with challenges. In this context, we present a strategic roadmap, tailored to your discerning vision, to address solutions to post-implementation challenges.

To Know More, Read Full Article @ https://ai-techpark.com/bsfi-rpa-and-ai/ 

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