In the ever-evolving landscape of software development, the integration of artificial intelligence (AI) has sparked both curiosity and concern regarding its potential impact on the role of software developers. As we navigate this transformative era, Andy Hilliard, CEO of Accelerance and a distinguished figure in the software industry, offers invaluable insights into the intricate relationship between AI and human expertise.
With a wealth of experience in facilitating global collaboration and optimizing software engineering teams, Hilliard brings a nuanced perspective to the forefront. As the author of the forthcoming book, “Synergea: A Blueprint for Building Effective, Globally Distributed Teams in the New Era of Software Development,” his expertise extends beyond conventional boundaries, encompassing the dynamics of remote teams, outsourcing partnerships, and the integration of AI into software development processes.
The question “Will AI make software developers obsolete?” resonates deeply within the industry, stirring debates and prompting introspection. Hilliard delves into this pressing inquiry in this interview, drawing upon his insights to explore the multifaceted implications of AI adoption in software development.
From addressing concerns surrounding data privacy and ethical considerations to advocating for the synergy between AI and human expertise, Hilliard navigates the complexities of this paradigm shift with clarity and foresight. Through his perspective, we gain a deeper understanding of the transformative potential of AI and its role in shaping the future of software development.
Join us as we embark on a thought-provoking journey with Andy Hilliard, exploring the intricate interplay between AI and human ingenuity and uncovering the possibilities in the evolving software development landscape.
1. In your upcoming book, “Synergea: A Blueprint for Building Effective, Globally Distributed Teams in the New Era of Software Development,” what are some key strategies you recommend for optimizing relationships between clients and outsourcing partners in the context of software engineering and product development teams?
It’s been proven that remote teams can perform just as well, or better, than traditional teams in a single location— and they spend less time around the proverbial water cooler. In addition to happier, healthier, and more productive workers, employers who embrace a remote-first working model benefit from lower staff turnover, lower overhead, and greater flexibility when searching for new and additional talent.
One potential issue in integrating offshore teams that we’ve seen is resentment or fear from onsite teams. They’re worried about losing their jobs to a possibly less costly resource. To help ease those tensions and improve chances for project success, leadership must be transparent about why an offshore team is being brought on. Often, it’s simply that HR can’t acquire needed experts quickly enough to meet needed goals. Maybe there’s a local talent shortage. But without that open communication about why an offshore team is being contracted, team members may be concerned – often for no reason – which drives conflict with the offshore team.
Nearshoring and offshoring software development have had little impact on unemployment rates and wage growth over the past several decades. Despite huge amounts of work going to countries like India, the Philippines, Vietnam, Argentina, and other countries, more people are working in technology in the U.S. than ever before, and there are still more than 1 million unfilled IT jobs here. Onsite team members need to know that.
Before embarking on an offshoring project, management needs alignment, commitment, and definitions around a distributed yet cohesive, cross-functional, outcome-driven, Agile organization, using common processes and technology to deliver measurable results aligned with business and operations objectives. Leadership must exercise transparency, clearly communicating the reasons for offshoring and addressing potential concerns about job security. They must ensure all internal stakeholders are aligned on project goals, roles, and responsibilities. They must have clarity, define and measure progress effectively, and establish smooth handoffs between internal and outsourced teams.
- Are expectations understood and agreed to by all internal team members?
- Are the right internal people assigned to the project?
- How will progress be defined and measured?
- How will you ensure that internal and outsourced team members’ handoffs don’t break down?
- Do you have a clear roadmap for the project?
Create an Offshore Delivery Center (ODC) to create that fully integrated, cohesive, cross-functional, outcome-driven, Agile organization. Enablement of this model comes from a structured alignment of
- Guiding principles, operating model, templates, definitions (terms, acronyms, etc.)
- Software development tools, productivity tools, communication protocols & tools
- Cultural and team building exercises.
Most companies are unaware of the proper preparation that should take place before entering an outsourcing engagement. Tech leaders who jump straight to partner selection overlook the potential—and often all too obvious—risk factors within their organization that could derail a project that would otherwise have been a slam dunk.
While I’m one of outsourcing’s biggest proponents, I’m not shy about telling executives at different companies not to do it until they get critical aspects of their business culture and processes, management and leadership structures, and technological resources and thought processes figured out in advance. The adage “go slow to go fast” applies to effective global software development. Companies are often so anxious to “flip a switch” and get results that they don’t realize the magnitude of value they are missing by establishing a solid relationship model, and they are inadvertently introducing a lot of risk in search of immediate gratification.
It’s much better to wait six months or even a year and have a successful outsourcing project than to start now and have a catastrophic failure on your hands.
2. As AI continues to shape the software development landscape, what measures do you suggest companies take to address challenges such as data privacy concerns and ethical considerations?
Start with “Privacy by Design”: Don’t think of privacy as an afterthought – bake it in from the initial planning stages. Figure out the absolute minimum data needed for your AI to work, and don’t collect more than that.
Be extra careful with sensitive data: Race, health information, etc., need additional safeguards. Anonymize or strongly encrypt it whenever possible. Have clear rules about who can access it and why.
Get informed consent: Let people know when their data is used how, and offer choices. Remember, even if it’s legal, it doesn’t mean it’s ethical, so give users genuine control.
Watch for bias: AI learns from data, and our data is full of societal biases. Test your systems constantly for unfair outcomes. Build diverse datasets and get input from people with varied backgrounds during development.
Explain those decisions: “The AI said so” isn’t acceptable. Especially for high-stakes uses (loans, healthcare), work towards explainability. Can you trace back how the AI concluded?
Stay accountable: Appoint a privacy/ethics team. Conduct regular audits. Accept that mistakes happen, but have a plan for how you’ll fix them and communicate with those affected.
3. Could you elaborate on the importance of fostering collaboration between AI and human expertise in software development? How do you envision this synergy influencing the future of the industry?
The future of software development isn’t human vs. machine but a partnership in which each plays a vital role. AI excels at generating flawless code with lightning speed, liberating us from tedium. Yet, true innovation demands more than technical perfection – it needs the human touch for deep context.
While AI automates the mundane, it can’t match the spark of creativity or the nuanced problem-solving born from experience. AI shines in speed, sometimes faltering in maintainability and security, where wisdom outweighs training data.
The future lies in collaboration. Let AI handle the grunt work! We, the human architects, must guide it to ensure code is secure, sustainable, and truly impactful. This isn’t just coding – it’s shaping the future. Let’s use AI as a powerful tool, not a replacement, to drive innovation that uplifts technology and humanity.
